aurimas13/Machine-Learning-Goodness

The Machine Learning project including ML/DL projects, notebooks, cheat codes of ML/DL, useful information on AI/AGI and codes or snippets/scripts/tasks with tips.

Jupyter Notebook

286

711 commits

updated Jan 5, 2026

See the code

README

Machine Learning Goodness with various repositories or notebooks, ML/DL projects and AGI/AI tips/cheats.


jupyter python lastcommit stars twitter twitter

Overview & Next Move

With the start of 100DaysOfMLCode challenge this Machine Learning Goodness repository is updated daily with either the completed Jupyter notebooks, Python codes, ML projects, useful ML/DL/NN libraries, repositories, cheat codes of ML/DL/NN/AI, useful information such as websites, beneficial learning materials, tips and whatnot not to mention some basic and advanced Python coding.

As the challenge is over the repo still grows. New beneficial material or materials in the world of Machine Learning when found is/are added to books, tools or repositories as well as updated in FinishYearWithML challenge and tweeted through my Twitter account and on Linkedin as well as sometimes on Facebook, Instagram.

Table of Contents

Worthy Books

(Back to top)

Worthy books to hone expertise of ML/DL/NN/AGI, Python Programming, CS fundamentals needed for AI analysis and any useful book for a Developer or ML Engineer.

NumberTitleDescriptionLink
1Grokking Algorithms: An illustrated guide for programmers and other curious peopleVisualisation of most popular algorithms used in Machine Learning and programming to solve problemsGrokking Algorithms
2Algorithm Design ManualIntroduction to mathematical analysis of a variety of computer algorithmsAlgorithm Design Manual
3Category Theory for ProgrammersBook about Category Theory written on posts from Milewski's programming cafeCategory Theory for Programmers
4Automated Machine LearningBook includes overviews of the bread-and-butter techniques we need in AutoML, provides in-depth discussions of existing AutoML systems, and evaluates the state of the art in AutoMLAutomated Machine Learning
5Mathematics for Computer ScienceBook by MIT on Mathematics for Computer ScienceMathematics for Computer Science
6Mathematics for Machine LearningBook by University of California on Mathematics for Machine LearningMathematics for Machine Learning
7Applied Artificial IntelligenceBook on engineering AI applicationsApplied Artificial Intelligence
8Automating Machine Learning PipelineBook-overview of automating ML lifecycle with Databricks Lakehouse platformAutomating Machine Learning Pipeline
9Machine Learning YearningThe book for AI Engineers win the era of Deep LearningMachine Learning Yearning
10Think BayesAn introduytion to Bayesian statistics with Python implementation and Jupyter NotebooksThink Bayes
11The Ultimate ChatGPT GuideThe book that provides 100 resources to enhance your life with ChatGPTThe Ultimate ChatGPT Guide
12The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective PromptsThe book to learn strategies for crafting compelling ChatGPT prompts that drive engaging and informative conversationsThe Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts
1310 ChatGPT prompts for Software EngineersThe book to learn how to prompt for software engineering tasks10 ChatGPT prompts for Software Engineers
14How to Build Your Career in AIAndrew Ng's insights about learning foundational skills, working on projects, finding jobs, and community in machineHow to Build Your Career in AI
15Machine Learning Q and AITh book on popular wuestions asked in interviews on ML and advanced information to those questionsMachine Learning Q and AI
16A comprehensive guide to Machine LearningA free book of comprehensive guide to MLA comprehensive guide to Machine Learning
17Math for Deep Learning: What You Need to Know to Understand Neural NetworksA book of Mathematics for Machine Learning and Artificial Intelligence that goes into the Mathematics & Statistics Foundations of for Data ScienceMath for Deep Learning: What You Need to Know to Understand Neural Networks

Worthy Tools

(Back to top)

Worthy websites and tools that include cheat codes for Python, Machine Learning, Deep Learning, Neural Networks and what not apart from other worthy tools while you are learning or honing your skills can be found here. Updated constantly when a worthy material is found to be shared on the repository.

NumberTitleDescriptionLink
1Python CheatsheetThe Python Cheatsheet based on the book "Automate the Boring Stuff with Python" and many other sourcesPython Cheatsheet
2Machine Learning Algorithms CheatsheetThe Machine Learning Cheatsheet explaining various models brieflyML Algorithms Cheatsheet
3Awesome AI Datasets & ToolsLinks to popular open-source and public datasets, data visualizations, data analytics resources, and data lakesAwesome AI Datasets & Tools
4Machine Learning CheatsheetThis Cheatsheet contains many classical equations and diagrams on Machine Learning to quickly recall knowledge and ideas on Machine LearningMachine Learning Cheatsheet
5Universal Intelligence: A Definition of Machine IntelligenceThe publication on definitions of intelligenceUniversal Intelligence
6Logistic RegressionDetailed Overview of Logistic RegressionLogistic Regression
7BCI OverviewSimple Overview of Brain-Computer Interface (BCI)BCI Overview
8BCI ResearchFascinating research of Brain-Computer Interface (BCI)BCI Research
9AI in Chemical DiscoveryHow AI is changing Chemical Diccovery?AI in Chemical Discovery
10Machine Learning for ChemistryBest practices in Machine Learning for ChemistryMachine Learning for Chemistry
11AI tools for drug discovery5 cool AI-powered Drug Discovery toolsAI tools for drug discovery
12Quantum Chemistry and Deep LearningThe application of Deep Learning and Neural Networks on Quantum ChemistyQuantum Chemistry and Deep Learning
13Computing Machinery and IntelligenceFirst paper on AI by Alan TuringComputing Machinery and Intelligence
14The blog on the take of Alan TuringThe analysis of Alan Turing's paper on AI (13 in the list) and the blog post on the life of himBlog on Alan Turing
15Minds, Brains and ProgramsPaper that objects 'Turing Test' by John SearleMinds, Brains and Programs
16The blog on the take Of John Searle & Alan TuringThe blog post on the take Of John Searle paper (15 in the list) and ideas about AI and Alan TuringJohn Searle & Alan Turing
17The Youtube channel on Deep Learning's Neural NetworksAn amazing youtube channel explaining what is Neural Network with simple and easy to follow descriptionsDeep Learning's Neural Networks
188 architectures of Neural Networks8 architectures of Neural Network every ML engineer should know8 architectures
19Neural Networks for the Prediction of Organic Chemistry ReactionsThe use of neural networks for predicting reaction typesNNs for Prediction of Organic Chemistry Reactions
20Expert System for Predicting Reaction Conditions: The Michael Reaction CaseModels were built to decide the compatibility of an organic chemistry process with each considered reaction condition optionExpert System for Predicting Reaction Conditions
21Machine Learning in Chemical Reaction SpaceLooked at reaction spaces of molecules involved in multiple reactions using ML-conceptsMachine Learning in Chemical Reaction Space
22Machine Learning for Chemical ReactionsAn overview of the questions that can and have been addressed using machine learning techniquesMachine Learning for Chemical Reactions
23ByTorch overviewBoTorch as a framework of PyTorchByTorch overview
24ByTorch officialBayesian optimization or simply an official website of BoTorchByTorch official
25VS Code CheatsheetVS Code Shortcut CheatsheetVS Code Cheatsheet
26Simple Machine Learning CheatsheetThe Machine Learning Cheatsheet of all fields making it and common used algorithmsMachine Learning Cheatsheet
27DeepMind & UCL on Reinforcement LearningDeepMind & UCL lectures as videos on Reinforcement LearningDeepMind & UCL on Reinforcement Learning
28Stanford Machine Learning Full CourseFull machine Learning course as lecture slides given at Stanford UniversityStanford Machine Learning Full Course
29Coursera's Deep Learning SpecializationDL Specialization given by teh great Andrew Ng and his team at deeplearning.aiCoursera's Deep Learning Specialization
30Simple Clustering CheatsheetSimple Unsupervised Learning Clustering CheatsheetClustering Cheatsheet
31Cheatsheet on Confusion MatrixCheatsheet on accuracy, precision, recall, TPR, FPR, specificity, sensitivity, ROC and all that stuff in Confusion matrixCheatsheet on Confusion Matrix
32Cheatsheets for Data ScientistsVarious and different cheatsheets for data scientistsCheatsheets for Data Scientists
33K-Means Clustering visualisationSimple graphics explaining K-Means ClusteringK-Means Clustering visualisation
34Youtube channel by 3Blue1BrownYoutube channel on animated math conceptsAnimated math concepts
35Essence of Linear AlgebraYoutube playlist on Linear Algebra by 3Blue1BrownLinear Algebra
36The Neuroscience of Reinforcment LearningThe Princeton slides of Neuroscience for Reinforcement LearningThe Neuroscience of Rein forcement Learning
37Reinforcement Learning of Drug DesignReinforcement Learning implementation of Drug DesignReinforcment Learning of Drug Design
38Brain-Computer Interface with backingAdvanced BCI with a flexible and moldable backing and penetrating microneedlesBrain-Computer Interface with backing
39Big O NotationGreat and simple explanation on Big O notationBig O Notation
406 Data Science Certificates6 Data Science Certificates to boost your career6 Data Science Certificates
41On the Measure of IntelligenceThe new concept to measure how human-like artificial intelligence isOn the Measure of Intelligence
42A Collection of Definitions of Intelligence70-odd definitions of intelligenceA Collection of Definitions of Intelligence
43Competition-Level Code Generation with AlphaCodeAlphaCode paperCompetition-Level Code Generation with AlphaCode
44Machine LearningWhat is Machine Learning? A well explained introdutionMachine Learning
45AutoencodersIntroduction to Autoencoders and dive into Undercomplete AutoencodersAutoencoders
46ChatGPT CheatsheetA must-have Cheatsheet for anyone that is using ChatGPT a lotChatGPT Cheatsheet
47Scikit-learn CheatsheetScikit-Learn Cheatsheet fo Machine LearningScikit-Learn Cheatsheet
48Top 13 Python Deep Learning LibrariesSummary of top libraries in Deep learning using PythonTop 13 Python Deep Learning Libraries
49A Simple Guide to Machine Learning VisualisationsSummary of visual inspection on ML models performanceA Simple Guide to Machine Learning Visualisations
50Discovering the systematic errors made by machine learning modelsSummary to discover errors on Machine Learning models that achieve high overall accuracy on coherent slices of validation dataDiscovering the systematic errors made by machine learning models
51Hypothesis Testing Explaine?Explanation of Hypothesis TestingA Simple Guide to Machine Learning Visualisations
52Intro Course to AIFree introductory AI course for beginner's given by MicrosoftIntro Course to AI
53ChatGPT productivity hacksChatGPT productivity hacks: Five ways to use chatbots to make your life easierChatGPT productivity hacks
54Triple Money with Data ScienceArticle on how a fellow tripled his income with Data Science in 18 MonthsTriple Money with Data Science
55Predictions on AI for the next 10 yearsAndrew Ng's prediction on AI for the next 10 yearsPredictions on AI for the next 10 years
56Theory of Mind May Have Spontaneously Emerged in Large Language ModelsPublication overviewing LLM models like ChatGPTTheory of Mind May Have Spontaneously Emerged in Large Language Models
57How ChatGPT Helps You To Automate Machine Learning?ChatGPT in Machine LearningHow ChatGPT Helps You To Automate Machine Learning?
58The ChatGPT Cheat SheetUn-official ChatGPT cheat sheetThe ChatGPT Cheat Sheet
59OpenAI CookbookOfficial ChatGPT cheat sheetOpenAI Cookbook
60Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to InterpretabilityGraph Machine Learning implementation in Drug DiscoveryKnowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability
61A Simple Guide to Machine Learning VisualisationsGuide to ML visualisationsA Simple Guide to Machine Learning Visualisations
62How to Visualize PyTorch Neural Networks – 3 Examples in Python3 examples of PyTorch visualisationsHow to Visualize PyTorch Neural Networks – 3 Examples in Python
63Role of Data Visualization in Machine LearningRole of visualisation in MLRole of Data Visualization in Machine Learning
64Interpreting A/B test results: false positives and statistical significanceInterpretation of A/B test resultsInterpreting A/B test results: false positives and statistical significance
65Complete Guide to A/B Testing Design, Implementation and PitfallsComplete Guide to A/B TestingComplete Guide to A/B Testing Design, Implementation and Pitfalls
66Tips for Data Scienists and DataEngineers in their interviewsTips for interviews by Seattle Data GuyTips for Data Scienists and DataEngineers in their interviews
67Git Cheat Sheet for Data ScienceCheat Sheet of Git commands for Data ScienceGit Cheat Sheet for Data Science
68CNN for Breast Cancer ClassificationOverview of an algorithm to automatically identify whether a patient is suffering from breast cancer or not by looking at biopsy imagesCNN for Breast Cancer Classification
69Goodhart’s LawOverview of Goodhart’s Law used at OpenAIGoodhart’s Law
70How to Build an ML Platform from ScratchStandard way to design, train and deploy modelHow to Build an ML Platform from Scratch
71Recap of Self-Supervised LearningOverview of Self-Supervised LearningRecap of Self-Supervised learning
72Recap of MLOps (2021)Overview of MLOpsRecap of MLOps (2021)
73Recap of MLOps (2020)Overview of MLOpsRecap of MLOps (2020)
74Art of Neural NetworksArtistic representations of Neural NetworksArt of Neural Networks
75Design patterns of MLOpsA summary of design patterns in MLOpsDesign patterns of MLOps
76How to Stay on Top of What’s Going on in the AI WorldResources on how to keep up with all the news and navigate through the endless stream of AI informationHow to Stay on Top of What’s Going on in the AI World
77ChatGPT and Whisper APIIntegration tool for developer of ChatGPT and Whisper APIChatGPT and Whisper API
7820 Machine Learning Projects That Will Get You HiredProjects thta should get you hired as an ML Engineer20 Machine Learning Projects That Will Get You Hired
797 Top Machine Learning Programming LanguagesTop programming languages used in Machine learning7 Top Machine Learning Programming Languages
80Effective Testing for Machine Learning Projects (Part I)Blog post on Effective Testing for ML projects (Part I)Effective Testing for Machine Learning Projects (Part I)
81Effective Testing for Machine Learning Projects (Part II)Blog post on Effective Testing for ML projects (Part II)Effective Testing for Machine Learning Projects (Part III)
82Effective Testing for Machine Learning Projects (Part III)Blog post on Effective Testing for ML projects (Part III)Effective Testing for Machine Learning Projects (Part III)
83Decision making at NetflixHow Netflix uses A/B tests to make decisions that continuously improve their products, so they can deliver more joy and satisfaction to membersDecision making at Netflix
84What is an A/B Test?How Netflix uses A/B tests to inform decisions and continuously innovate on their productsWhat is an A/B Test?
85Interpreting A/B test results: false positives and statistical significanceInterpreting A/B test results by looking at false positives and statistical significanceInterpreting A/B test results: false positives and statistical significance
86Complete Guide to A/B Testing Design, Implementation and PitfallsEnd-to-end A/B testing for your Data Science experiments for non-technical and technical specialists with examples and Python implementationComplete Guide to A/B Testing Design, Implementation and Pitfalls.
8710 Statistical Concepts You Should Know For Data Science InterviewsStatistical Concepts necessary to be known for Data Science interviews10 Statistical Concepts You Should Know For Data Science Interviews.
88Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and RecallOverview of evaluating ML models with metrics of Confusion Matrix, Accuracy, Precision, and RecallEvaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall
89Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?Perspective of AI in MedicineArtificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?
90Graph Neural Network in Drug DiscoveryDeep Learning application to transform Drug Discovery process to increase the efficiency in finding new compoundsGraph Neural Network in Drug Discovery
91New AI approach to reduce noise in X-ray dataOverview of the usage of autoencoders to replace noisy X-ray data with noise-free input signalsNew AI approach to reduce noise in X-ray data
92Natural Language ProcessingThe guide covers how it works, where it is applied top technques and moreNatural Language Processing
93Big O CheatsheetBig O Cheatsheet for Data Structures #1Big O Cheatsheet
94Big O CheatsheetBig O Cheatsheet for Data Structures #2Big O Cheatsheet
95A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPTA historical overview of generative AI techniques and applicationsA Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
96ChatDoctorA Medical Chat Model Fine-tuned on LLaMA Model using Medical Domain KnowledgeChatDoctor
97ALL CHEAT SHEETCheatsheets from Artificial Intelligence to Data Engineering to Machine Learning to Linux to Mathematics to R to Matlab and many more fieldsALL CHEAT SHEET
98GMAIPaper on a Generalist Medical AI (GMAI) to drive the development of large-scale medical AI models, increase accuracy on medical tasks, make complex medical information easier to access and assist surgical teamsGMAI
999 essential ChatGPT prompts9 essential ChatGPT prompts with examples9 essential ChatGPT prompt
100IPython ChatGPT extensionExtension that allows you to use ChatGPT directly from your Jupyter Notebook or IPython ShellIPython ChatGPT extension
101OpenAssistantOpen-source alternative to ChatGPTOpenAssistant
102DINOv2Unsupervised Vision Transformer Model can be used as a backbone for almost all your CV tasksDINOv2
103DatamolOpen-source toolkit that simplifies molecular processing and featurization workflows for ML scientists in drug discoveryDatamol
104ChatGPT vs GPT4 comparisonImage comparing ChatGPT with GPTChatGPT vs GPT4 comparison
105Self-Supervised Learning CookbookResearch and all the notes on the dark matter of intelligenceSelf-Supervised Learning Cookbook
106Prompt Engineering Cheat SheetHelping to write great prompts to Chat Bots like GPTPrompt Engineering Cheat Sheet
107GitHub Copilot GuideGitHub Copilot Guide as slidesGitHub Copilot Guide
108Comparison of GitHub Copilot with ChatGPTComparison of a chatbot with a programming helper as slidesComparison of GitHub Copilot with ChatGPT
109Comparison of GitHub Copilot with CodeiumComparison of coding helpers; one payable, other open sourceComparison of GitHub Copilot with Codeium
110Getting started with AutoGPTGetting started with AutoGPT - Insallation - Use Cases - Possibl MisuseGetting started with AutoGPT - Insallation - Use Cases - Possibl Misuse
111Useful AI ToolsUseful AI Tools from Copilot to AutoGPT to MidJourney to Grammarly to converational botsUseful AI Tools from Copilot to AutoGPT to MidJourney to Grammarly to converational bots
112ChatGPT Prompting Cheat SheetCheatsheet of useful ChatGPT promptsChatGPT Prompting Cheat Sheet
113MACHINE LEARNING A First Course for Engineers and ScientistsMachine Learning beginner to advaned informaton from Cambridge UniversityMACHINE LEARNING A First Course for Engineers and Scientists.
114Machine Learning ProjectsMachine Learning ProjectsMachine Learning Projects
115Python Data Science HandbookPython Data Science HandbookPython Data Science Handbook
116An Introduction to Statistics with PythonStatistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of dataAn Introduction to Statistics with Python
117Python for EverybodyPython for EverybodyPython for Everybody
118Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series)Machine Learning with Python for EveryoneMachine Learning with Python for Everyone
119Python for Data AnalysisPython for Data AnalysisPython for Data Analysis
120Python Data Science EssentialsPython Data Science EssentialsPython Data Science Essentials
121Graph Data Modeling with PythonGraph Data Modeling with PythonGraph Data Modeling with Python
12250 Days of Python — A Challenge a Day.50 Days of Python — A Challenge a Day.50 Days of Python — A Challenge a Day.
123Tiny Python ProjectsTiny Python ProjectsTiny Python Projects
124Mind Blowing AI toolsAI tools from writing to video to design to productivity to marketing to ChatbotMind Blowing AI tools
125150+ Python Projects with Source Code179 Python Projects with Source Code150+ Python Projects with Source Code
1261000 ChatGPT useful prompts1000 ChatGPT useful prompts1000 ChatGPT useful prompts

Worthy Repositories

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Worthy GitHub repositories related to the ML/DL/NN/AGI courses with all details included can be found here:

NumberTitleDescriptionLink
1Advanced AI courseCode Academy Advanced AI course in LithuaniaAdvanced AI course
2GitHub on Coursera's Deep Learning CourseGitHub Repo for Coursera's Deep Learning Specialization by deeplearning.aiGitHub on Coursera's DL Course
3Notes on Coursera's Deep Learning CourseLecture Notes for Coursera's Deep Learning Specialization by deeplearning.aiNotes on Cousera's DL Course
4Category Theory on Machine LearningGithub containing list of publications of Category Theory in various AI fieldsCategory Theory on ML
5Foundations of Machine LearningUnderstand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine LearningFoundations of ML
6Awesome RLGithub repository on amazing materials on Reinforcement LearningAwesome RL
7Optimizing Chemical ReactionsOptimizing Chemical Reactions with Deep Reinforcement LearningOptimizing Chemical Reactions
8Machine Learning cheatsheetsMachine Learning cheatsheets on Supervised, Unsupervised & Deep Learning as well as Tips and TricksMachine Learning cheatsheets
9ML Youtube CoursesMost recent Machine Leaning courses available on YoutubeML Youtube Course
10Machine Learning Course NotesNotes on the courses related to Machine LearningMachine Learning Course Notes
11Effective Testing for ML ProjectsGitHub repository for Effective Testing for ML ProjectsEffective Testing for ML Projects
12ChatDoctorGitHub repository for ChatDoctor while it is written about it on 90th day or accessed as 96 item on toolChatDoctor GitHub
13Auto-GPTGitHub repository of an experimetal application showcasing the capabilites of GPt4Auto-GPT
14Vicuna-13BAn open-source chatbot trained by fine-tuning LLaMA on ~70K user-shared ChatGPT conversationsVicuna-13B
15Prompt Engineering GuidePrompt Engineering GuidePrompt Engineering Guide
16Best-of Machine Learning with Python910 curated ML projectsBest-of Machine Learning with Python
17Data Science for Beginners - A CurriculumAzure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data ScienceData Science for Beginners - A Curriculum
18Data-Science-Interview-ResourcesData Science Interview ResourcesData-Science-Interview-Resources
19AWESOME DATA SCIENCEOpen source Data Science repository to learn and apply data science skills towards solving real world problemsAWESOME DATA SCIENCE
20DatamolOpen-source toolkit that simplifies molecular processing and featurization workflows for ML scientists in drug discoveryDatamol
21privateGPTA magical tool where you can ask questions to your documents without an internet connection by just using the power of LLMsprivateGPT
22RT-2 modleA model that uses up to 55B params backbone and fine-tunes it to directly output robot actions that are executed in the real worldRT-2
23GPTCacheA tool that allows you to cache the results of GPT-3 API calls and reuse them laterGPTCache
24Awesome AI-Powered Developer ToolsTools that leverage AI to assist developers in tasks such as code completion, refactoring, debugging, documentation, and moreAwesome AI-Powered Developer Tools

Notebooks

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Done notebooks of various datasets can be found here.

Notes

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Additional notes that we covered through lectures or material that I mentioned and spoke about can be found here.

100DaysOfMLCode

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Materials from the challenge of #100DaysOfMLCode for each day can be found here under README section there.

FinishYearWithML

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Materials from the challenge of #FinishYearWithML for each day can be found here under README section there.

Public

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Public folder contains two files:

Jupyter in Browser

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First nice thing is that you could run Jupyter also through browser by doing so going here and reading more about it in this article.

If you find difficulty in running Jupyter Notebook through Browser then you could use Google Colab by clicking here. Functionalities of both machines are similar.

Logo

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The Logo of the repository can be found here.

License

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The MIT LICENSE can be found here.

algorithms
artifcial-intelligence
artificial-intelligence
chatgpt
cheatsheets
computer-science
data-science
deep-neural-networks
deep-reinforcement-learning
gpt4
machine-learning
machine-learning-algorithms
mlops
python
python3
reinforcement-learning
reinforcement-learning-algorithms
tips
tips-and-tricks

Contributors

aurimas13

711 commits

aurimas13/Machine-Learning-Goodness

The Machine Learning project including ML/DL projects, notebooks, cheat codes of ML/DL, useful information on AI/AGI and codes or snippets/scripts/tasks with tips.

Jupyter Notebook

286

711 commits

updated Jan 5, 2026

See the code

README

Machine Learning Goodness with various repositories or notebooks, ML/DL projects and AGI/AI tips/cheats.


jupyter python lastcommit stars twitter twitter

Overview & Next Move

With the start of 100DaysOfMLCode challenge this Machine Learning Goodness repository is updated daily with either the completed Jupyter notebooks, Python codes, ML projects, useful ML/DL/NN libraries, repositories, cheat codes of ML/DL/NN/AI, useful information such as websites, beneficial learning materials, tips and whatnot not to mention some basic and advanced Python coding.

As the challenge is over the repo still grows. New beneficial material or materials in the world of Machine Learning when found is/are added to books, tools or repositories as well as updated in FinishYearWithML challenge and tweeted through my Twitter account and on Linkedin as well as sometimes on Facebook, Instagram.

Table of Contents

Worthy Books

(Back to top)

Worthy books to hone expertise of ML/DL/NN/AGI, Python Programming, CS fundamentals needed for AI analysis and any useful book for a Developer or ML Engineer.

NumberTitleDescriptionLink
1Grokking Algorithms: An illustrated guide for programmers and other curious peopleVisualisation of most popular algorithms used in Machine Learning and programming to solve problemsGrokking Algorithms
2Algorithm Design ManualIntroduction to mathematical analysis of a variety of computer algorithmsAlgorithm Design Manual
3Category Theory for ProgrammersBook about Category Theory written on posts from Milewski's programming cafeCategory Theory for Programmers
4Automated Machine LearningBook includes overviews of the bread-and-butter techniques we need in AutoML, provides in-depth discussions of existing AutoML systems, and evaluates the state of the art in AutoMLAutomated Machine Learning
5Mathematics for Computer ScienceBook by MIT on Mathematics for Computer ScienceMathematics for Computer Science
6Mathematics for Machine LearningBook by University of California on Mathematics for Machine LearningMathematics for Machine Learning
7Applied Artificial IntelligenceBook on engineering AI applicationsApplied Artificial Intelligence
8Automating Machine Learning PipelineBook-overview of automating ML lifecycle with Databricks Lakehouse platformAutomating Machine Learning Pipeline
9Machine Learning YearningThe book for AI Engineers win the era of Deep LearningMachine Learning Yearning
10Think BayesAn introduytion to Bayesian statistics with Python implementation and Jupyter NotebooksThink Bayes
11The Ultimate ChatGPT GuideThe book that provides 100 resources to enhance your life with ChatGPTThe Ultimate ChatGPT Guide
12The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective PromptsThe book to learn strategies for crafting compelling ChatGPT prompts that drive engaging and informative conversationsThe Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts
1310 ChatGPT prompts for Software EngineersThe book to learn how to prompt for software engineering tasks10 ChatGPT prompts for Software Engineers
14How to Build Your Career in AIAndrew Ng's insights about learning foundational skills, working on projects, finding jobs, and community in machineHow to Build Your Career in AI
15Machine Learning Q and AITh book on popular wuestions asked in interviews on ML and advanced information to those questionsMachine Learning Q and AI
16A comprehensive guide to Machine LearningA free book of comprehensive guide to MLA comprehensive guide to Machine Learning
17Math for Deep Learning: What You Need to Know to Understand Neural NetworksA book of Mathematics for Machine Learning and Artificial Intelligence that goes into the Mathematics & Statistics Foundations of for Data ScienceMath for Deep Learning: What You Need to Know to Understand Neural Networks

Worthy Tools

(Back to top)

Worthy websites and tools that include cheat codes for Python, Machine Learning, Deep Learning, Neural Networks and what not apart from other worthy tools while you are learning or honing your skills can be found here. Updated constantly when a worthy material is found to be shared on the repository.

NumberTitleDescriptionLink
1Python CheatsheetThe Python Cheatsheet based on the book "Automate the Boring Stuff with Python" and many other sourcesPython Cheatsheet
2Machine Learning Algorithms CheatsheetThe Machine Learning Cheatsheet explaining various models brieflyML Algorithms Cheatsheet
3Awesome AI Datasets & ToolsLinks to popular open-source and public datasets, data visualizations, data analytics resources, and data lakesAwesome AI Datasets & Tools
4Machine Learning CheatsheetThis Cheatsheet contains many classical equations and diagrams on Machine Learning to quickly recall knowledge and ideas on Machine LearningMachine Learning Cheatsheet
5Universal Intelligence: A Definition of Machine IntelligenceThe publication on definitions of intelligenceUniversal Intelligence
6Logistic RegressionDetailed Overview of Logistic RegressionLogistic Regression
7BCI OverviewSimple Overview of Brain-Computer Interface (BCI)BCI Overview
8BCI ResearchFascinating research of Brain-Computer Interface (BCI)BCI Research
9AI in Chemical DiscoveryHow AI is changing Chemical Diccovery?AI in Chemical Discovery
10Machine Learning for ChemistryBest practices in Machine Learning for ChemistryMachine Learning for Chemistry
11AI tools for drug discovery5 cool AI-powered Drug Discovery toolsAI tools for drug discovery
12Quantum Chemistry and Deep LearningThe application of Deep Learning and Neural Networks on Quantum ChemistyQuantum Chemistry and Deep Learning
13Computing Machinery and IntelligenceFirst paper on AI by Alan TuringComputing Machinery and Intelligence
14The blog on the take of Alan TuringThe analysis of Alan Turing's paper on AI (13 in the list) and the blog post on the life of himBlog on Alan Turing
15Minds, Brains and ProgramsPaper that objects 'Turing Test' by John SearleMinds, Brains and Programs
16The blog on the take Of John Searle & Alan TuringThe blog post on the take Of John Searle paper (15 in the list) and ideas about AI and Alan TuringJohn Searle & Alan Turing
17The Youtube channel on Deep Learning's Neural NetworksAn amazing youtube channel explaining what is Neural Network with simple and easy to follow descriptionsDeep Learning's Neural Networks
188 architectures of Neural Networks8 architectures of Neural Network every ML engineer should know8 architectures
19Neural Networks for the Prediction of Organic Chemistry ReactionsThe use of neural networks for predicting reaction typesNNs for Prediction of Organic Chemistry Reactions
20Expert System for Predicting Reaction Conditions: The Michael Reaction CaseModels were built to decide the compatibility of an organic chemistry process with each considered reaction condition optionExpert System for Predicting Reaction Conditions
21Machine Learning in Chemical Reaction SpaceLooked at reaction spaces of molecules involved in multiple reactions using ML-conceptsMachine Learning in Chemical Reaction Space
22Machine Learning for Chemical ReactionsAn overview of the questions that can and have been addressed using machine learning techniquesMachine Learning for Chemical Reactions
23ByTorch overviewBoTorch as a framework of PyTorchByTorch overview
24ByTorch officialBayesian optimization or simply an official website of BoTorchByTorch official
25VS Code CheatsheetVS Code Shortcut CheatsheetVS Code Cheatsheet
26Simple Machine Learning CheatsheetThe Machine Learning Cheatsheet of all fields making it and common used algorithmsMachine Learning Cheatsheet
27DeepMind & UCL on Reinforcement LearningDeepMind & UCL lectures as videos on Reinforcement LearningDeepMind & UCL on Reinforcement Learning
28Stanford Machine Learning Full CourseFull machine Learning course as lecture slides given at Stanford UniversityStanford Machine Learning Full Course
29Coursera's Deep Learning SpecializationDL Specialization given by teh great Andrew Ng and his team at deeplearning.aiCoursera's Deep Learning Specialization
30Simple Clustering CheatsheetSimple Unsupervised Learning Clustering CheatsheetClustering Cheatsheet
31Cheatsheet on Confusion MatrixCheatsheet on accuracy, precision, recall, TPR, FPR, specificity, sensitivity, ROC and all that stuff in Confusion matrixCheatsheet on Confusion Matrix
32Cheatsheets for Data ScientistsVarious and different cheatsheets for data scientistsCheatsheets for Data Scientists
33K-Means Clustering visualisationSimple graphics explaining K-Means ClusteringK-Means Clustering visualisation
34Youtube channel by 3Blue1BrownYoutube channel on animated math conceptsAnimated math concepts
35Essence of Linear AlgebraYoutube playlist on Linear Algebra by 3Blue1BrownLinear Algebra
36The Neuroscience of Reinforcment LearningThe Princeton slides of Neuroscience for Reinforcement LearningThe Neuroscience of Rein forcement Learning
37Reinforcement Learning of Drug DesignReinforcement Learning implementation of Drug DesignReinforcment Learning of Drug Design
38Brain-Computer Interface with backingAdvanced BCI with a flexible and moldable backing and penetrating microneedlesBrain-Computer Interface with backing
39Big O NotationGreat and simple explanation on Big O notationBig O Notation
406 Data Science Certificates6 Data Science Certificates to boost your career6 Data Science Certificates
41On the Measure of IntelligenceThe new concept to measure how human-like artificial intelligence isOn the Measure of Intelligence
42A Collection of Definitions of Intelligence70-odd definitions of intelligenceA Collection of Definitions of Intelligence
43Competition-Level Code Generation with AlphaCodeAlphaCode paperCompetition-Level Code Generation with AlphaCode
44Machine LearningWhat is Machine Learning? A well explained introdutionMachine Learning
45AutoencodersIntroduction to Autoencoders and dive into Undercomplete AutoencodersAutoencoders
46ChatGPT CheatsheetA must-have Cheatsheet for anyone that is using ChatGPT a lotChatGPT Cheatsheet
47Scikit-learn CheatsheetScikit-Learn Cheatsheet fo Machine LearningScikit-Learn Cheatsheet
48Top 13 Python Deep Learning LibrariesSummary of top libraries in Deep learning using PythonTop 13 Python Deep Learning Libraries
49A Simple Guide to Machine Learning VisualisationsSummary of visual inspection on ML models performanceA Simple Guide to Machine Learning Visualisations
50Discovering the systematic errors made by machine learning modelsSummary to discover errors on Machine Learning models that achieve high overall accuracy on coherent slices of validation dataDiscovering the systematic errors made by machine learning models
51Hypothesis Testing Explaine?Explanation of Hypothesis TestingA Simple Guide to Machine Learning Visualisations
52Intro Course to AIFree introductory AI course for beginner's given by MicrosoftIntro Course to AI
53ChatGPT productivity hacksChatGPT productivity hacks: Five ways to use chatbots to make your life easierChatGPT productivity hacks
54Triple Money with Data ScienceArticle on how a fellow tripled his income with Data Science in 18 MonthsTriple Money with Data Science
55Predictions on AI for the next 10 yearsAndrew Ng's prediction on AI for the next 10 yearsPredictions on AI for the next 10 years
56Theory of Mind May Have Spontaneously Emerged in Large Language ModelsPublication overviewing LLM models like ChatGPTTheory of Mind May Have Spontaneously Emerged in Large Language Models
57How ChatGPT Helps You To Automate Machine Learning?ChatGPT in Machine LearningHow ChatGPT Helps You To Automate Machine Learning?
58The ChatGPT Cheat SheetUn-official ChatGPT cheat sheetThe ChatGPT Cheat Sheet
59OpenAI CookbookOfficial ChatGPT cheat sheetOpenAI Cookbook
60Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to InterpretabilityGraph Machine Learning implementation in Drug DiscoveryKnowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability
61A Simple Guide to Machine Learning VisualisationsGuide to ML visualisationsA Simple Guide to Machine Learning Visualisations
62How to Visualize PyTorch Neural Networks – 3 Examples in Python3 examples of PyTorch visualisationsHow to Visualize PyTorch Neural Networks – 3 Examples in Python
63Role of Data Visualization in Machine LearningRole of visualisation in MLRole of Data Visualization in Machine Learning
64Interpreting A/B test results: false positives and statistical significanceInterpretation of A/B test resultsInterpreting A/B test results: false positives and statistical significance
65Complete Guide to A/B Testing Design, Implementation and PitfallsComplete Guide to A/B TestingComplete Guide to A/B Testing Design, Implementation and Pitfalls
66Tips for Data Scienists and DataEngineers in their interviewsTips for interviews by Seattle Data GuyTips for Data Scienists and DataEngineers in their interviews
67Git Cheat Sheet for Data ScienceCheat Sheet of Git commands for Data ScienceGit Cheat Sheet for Data Science
68CNN for Breast Cancer ClassificationOverview of an algorithm to automatically identify whether a patient is suffering from breast cancer or not by looking at biopsy imagesCNN for Breast Cancer Classification
69Goodhart’s LawOverview of Goodhart’s Law used at OpenAIGoodhart’s Law
70How to Build an ML Platform from ScratchStandard way to design, train and deploy modelHow to Build an ML Platform from Scratch
71Recap of Self-Supervised LearningOverview of Self-Supervised LearningRecap of Self-Supervised learning
72Recap of MLOps (2021)Overview of MLOpsRecap of MLOps (2021)
73Recap of MLOps (2020)Overview of MLOpsRecap of MLOps (2020)
74Art of Neural NetworksArtistic representations of Neural NetworksArt of Neural Networks
75Design patterns of MLOpsA summary of design patterns in MLOpsDesign patterns of MLOps
76How to Stay on Top of What’s Going on in the AI WorldResources on how to keep up with all the news and navigate through the endless stream of AI informationHow to Stay on Top of What’s Going on in the AI World
77ChatGPT and Whisper APIIntegration tool for developer of ChatGPT and Whisper APIChatGPT and Whisper API
7820 Machine Learning Projects That Will Get You HiredProjects thta should get you hired as an ML Engineer20 Machine Learning Projects That Will Get You Hired
797 Top Machine Learning Programming LanguagesTop programming languages used in Machine learning7 Top Machine Learning Programming Languages
80Effective Testing for Machine Learning Projects (Part I)Blog post on Effective Testing for ML projects (Part I)Effective Testing for Machine Learning Projects (Part I)
81Effective Testing for Machine Learning Projects (Part II)Blog post on Effective Testing for ML projects (Part II)Effective Testing for Machine Learning Projects (Part III)
82Effective Testing for Machine Learning Projects (Part III)Blog post on Effective Testing for ML projects (Part III)Effective Testing for Machine Learning Projects (Part III)
83Decision making at NetflixHow Netflix uses A/B tests to make decisions that continuously improve their products, so they can deliver more joy and satisfaction to membersDecision making at Netflix
84What is an A/B Test?How Netflix uses A/B tests to inform decisions and continuously innovate on their productsWhat is an A/B Test?
85Interpreting A/B test results: false positives and statistical significanceInterpreting A/B test results by looking at false positives and statistical significanceInterpreting A/B test results: false positives and statistical significance
86Complete Guide to A/B Testing Design, Implementation and PitfallsEnd-to-end A/B testing for your Data Science experiments for non-technical and technical specialists with examples and Python implementationComplete Guide to A/B Testing Design, Implementation and Pitfalls.
8710 Statistical Concepts You Should Know For Data Science InterviewsStatistical Concepts necessary to be known for Data Science interviews10 Statistical Concepts You Should Know For Data Science Interviews.
88Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and RecallOverview of evaluating ML models with metrics of Confusion Matrix, Accuracy, Precision, and RecallEvaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall
89Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?Perspective of AI in MedicineArtificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?
90Graph Neural Network in Drug DiscoveryDeep Learning application to transform Drug Discovery process to increase the efficiency in finding new compoundsGraph Neural Network in Drug Discovery
91New AI approach to reduce noise in X-ray dataOverview of the usage of autoencoders to replace noisy X-ray data with noise-free input signalsNew AI approach to reduce noise in X-ray data
92Natural Language ProcessingThe guide covers how it works, where it is applied top technques and moreNatural Language Processing
93Big O CheatsheetBig O Cheatsheet for Data Structures #1Big O Cheatsheet
94Big O CheatsheetBig O Cheatsheet for Data Structures #2Big O Cheatsheet
95A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPTA historical overview of generative AI techniques and applicationsA Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
96ChatDoctorA Medical Chat Model Fine-tuned on LLaMA Model using Medical Domain KnowledgeChatDoctor
97ALL CHEAT SHEETCheatsheets from Artificial Intelligence to Data Engineering to Machine Learning to Linux to Mathematics to R to Matlab and many more fieldsALL CHEAT SHEET
98GMAIPaper on a Generalist Medical AI (GMAI) to drive the development of large-scale medical AI models, increase accuracy on medical tasks, make complex medical information easier to access and assist surgical teamsGMAI
999 essential ChatGPT prompts9 essential ChatGPT prompts with examples9 essential ChatGPT prompt
100IPython ChatGPT extensionExtension that allows you to use ChatGPT directly from your Jupyter Notebook or IPython ShellIPython ChatGPT extension
101OpenAssistantOpen-source alternative to ChatGPTOpenAssistant
102DINOv2Unsupervised Vision Transformer Model can be used as a backbone for almost all your CV tasksDINOv2
103DatamolOpen-source toolkit that simplifies molecular processing and featurization workflows for ML scientists in drug discoveryDatamol
104ChatGPT vs GPT4 comparisonImage comparing ChatGPT with GPTChatGPT vs GPT4 comparison
105Self-Supervised Learning CookbookResearch and all the notes on the dark matter of intelligenceSelf-Supervised Learning Cookbook
106Prompt Engineering Cheat SheetHelping to write great prompts to Chat Bots like GPTPrompt Engineering Cheat Sheet
107GitHub Copilot GuideGitHub Copilot Guide as slidesGitHub Copilot Guide
108Comparison of GitHub Copilot with ChatGPTComparison of a chatbot with a programming helper as slidesComparison of GitHub Copilot with ChatGPT
109Comparison of GitHub Copilot with CodeiumComparison of coding helpers; one payable, other open sourceComparison of GitHub Copilot with Codeium
110Getting started with AutoGPTGetting started with AutoGPT - Insallation - Use Cases - Possibl MisuseGetting started with AutoGPT - Insallation - Use Cases - Possibl Misuse
111Useful AI ToolsUseful AI Tools from Copilot to AutoGPT to MidJourney to Grammarly to converational botsUseful AI Tools from Copilot to AutoGPT to MidJourney to Grammarly to converational bots
112ChatGPT Prompting Cheat SheetCheatsheet of useful ChatGPT promptsChatGPT Prompting Cheat Sheet
113MACHINE LEARNING A First Course for Engineers and ScientistsMachine Learning beginner to advaned informaton from Cambridge UniversityMACHINE LEARNING A First Course for Engineers and Scientists.
114Machine Learning ProjectsMachine Learning ProjectsMachine Learning Projects
115Python Data Science HandbookPython Data Science HandbookPython Data Science Handbook
116An Introduction to Statistics with PythonStatistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of dataAn Introduction to Statistics with Python
117Python for EverybodyPython for EverybodyPython for Everybody
118Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series)Machine Learning with Python for EveryoneMachine Learning with Python for Everyone
119Python for Data AnalysisPython for Data AnalysisPython for Data Analysis
120Python Data Science EssentialsPython Data Science EssentialsPython Data Science Essentials
121Graph Data Modeling with PythonGraph Data Modeling with PythonGraph Data Modeling with Python
12250 Days of Python — A Challenge a Day.50 Days of Python — A Challenge a Day.50 Days of Python — A Challenge a Day.
123Tiny Python ProjectsTiny Python ProjectsTiny Python Projects
124Mind Blowing AI toolsAI tools from writing to video to design to productivity to marketing to ChatbotMind Blowing AI tools
125150+ Python Projects with Source Code179 Python Projects with Source Code150+ Python Projects with Source Code
1261000 ChatGPT useful prompts1000 ChatGPT useful prompts1000 ChatGPT useful prompts

Worthy Repositories

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Worthy GitHub repositories related to the ML/DL/NN/AGI courses with all details included can be found here:

NumberTitleDescriptionLink
1Advanced AI courseCode Academy Advanced AI course in LithuaniaAdvanced AI course
2GitHub on Coursera's Deep Learning CourseGitHub Repo for Coursera's Deep Learning Specialization by deeplearning.aiGitHub on Coursera's DL Course
3Notes on Coursera's Deep Learning CourseLecture Notes for Coursera's Deep Learning Specialization by deeplearning.aiNotes on Cousera's DL Course
4Category Theory on Machine LearningGithub containing list of publications of Category Theory in various AI fieldsCategory Theory on ML
5Foundations of Machine LearningUnderstand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine LearningFoundations of ML
6Awesome RLGithub repository on amazing materials on Reinforcement LearningAwesome RL
7Optimizing Chemical ReactionsOptimizing Chemical Reactions with Deep Reinforcement LearningOptimizing Chemical Reactions
8Machine Learning cheatsheetsMachine Learning cheatsheets on Supervised, Unsupervised & Deep Learning as well as Tips and TricksMachine Learning cheatsheets
9ML Youtube CoursesMost recent Machine Leaning courses available on YoutubeML Youtube Course
10Machine Learning Course NotesNotes on the courses related to Machine LearningMachine Learning Course Notes
11Effective Testing for ML ProjectsGitHub repository for Effective Testing for ML ProjectsEffective Testing for ML Projects
12ChatDoctorGitHub repository for ChatDoctor while it is written about it on 90th day or accessed as 96 item on toolChatDoctor GitHub
13Auto-GPTGitHub repository of an experimetal application showcasing the capabilites of GPt4Auto-GPT
14Vicuna-13BAn open-source chatbot trained by fine-tuning LLaMA on ~70K user-shared ChatGPT conversationsVicuna-13B
15Prompt Engineering GuidePrompt Engineering GuidePrompt Engineering Guide
16Best-of Machine Learning with Python910 curated ML projectsBest-of Machine Learning with Python
17Data Science for Beginners - A CurriculumAzure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data ScienceData Science for Beginners - A Curriculum
18Data-Science-Interview-ResourcesData Science Interview ResourcesData-Science-Interview-Resources
19AWESOME DATA SCIENCEOpen source Data Science repository to learn and apply data science skills towards solving real world problemsAWESOME DATA SCIENCE
20DatamolOpen-source toolkit that simplifies molecular processing and featurization workflows for ML scientists in drug discoveryDatamol
21privateGPTA magical tool where you can ask questions to your documents without an internet connection by just using the power of LLMsprivateGPT
22RT-2 modleA model that uses up to 55B params backbone and fine-tunes it to directly output robot actions that are executed in the real worldRT-2
23GPTCacheA tool that allows you to cache the results of GPT-3 API calls and reuse them laterGPTCache
24Awesome AI-Powered Developer ToolsTools that leverage AI to assist developers in tasks such as code completion, refactoring, debugging, documentation, and moreAwesome AI-Powered Developer Tools

Notebooks

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Done notebooks of various datasets can be found here.

Notes

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Additional notes that we covered through lectures or material that I mentioned and spoke about can be found here.

100DaysOfMLCode

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Materials from the challenge of #100DaysOfMLCode for each day can be found here under README section there.

FinishYearWithML

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Materials from the challenge of #FinishYearWithML for each day can be found here under README section there.

Public

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Public folder contains two files:

Jupyter in Browser

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First nice thing is that you could run Jupyter also through browser by doing so going here and reading more about it in this article.

If you find difficulty in running Jupyter Notebook through Browser then you could use Google Colab by clicking here. Functionalities of both machines are similar.

Logo

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The Logo of the repository can be found here.

License

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The MIT LICENSE can be found here.

algorithms
artifcial-intelligence
artificial-intelligence
chatgpt
cheatsheets
computer-science
data-science
deep-neural-networks
deep-reinforcement-learning
gpt4
machine-learning
machine-learning-algorithms
mlops
python
python3
reinforcement-learning
reinforcement-learning-algorithms
tips
tips-and-tricks

Contributors

aurimas13

711 commits

Languages

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