README
Yessenov Data Lab 2026
My work from Yessenov Data Lab — a 4-week intensive Machine Learning & Data Science program by the Shakhmardan Yessenov Foundation (Kazakhstan, summer 2026).
Each DayN/ folder is one day of the program: labs, project briefs and my solutions.
Program structure
| Week | Days | Topics | Course materials |
|---|---|---|---|
| 1 | Day1–5 | Python, EDA, first ML models (Titanic regression), RAG mini-app | timurbakibayev/ydl-2026 |
| 2 | Day6–10 | Applied ML: sensor data analysis, regression project, HAR team project, Kaggle-style ensemble pipeline | timurbakibayev/ydl-2026 |
| 3 | Day11–15 | Deep learning: NLP, architectures (CLIP), transformers, multimodal capstone | cillustrisimo/ydl_2026 |
| 4 | Day16–20 | Practical AI engineering: agents from scratch, OpenAI Agents SDK, tools & memory, multi-agent systems, RAG | saedhussain/practical_ai_engineering |
Highlights
- Day15 — capstone: multimodal sarcasm detection (MMSD2.0). Text + image classification
- Day12 — CLIP image search — semantic image search engine. Video demo
- Day13 — RU → EN translator built with transformers. Video demo
- Day9 — full Kaggle pipeline: EDA → baseline → feature engineering → CatBoost / MLP / SVM ensembles.
- Day17 — job search agent built with the OpenAI Agents SDK.
Contributors
rassulz
26 commits
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Languages
Jupyter Notebook
94.5%
Python
2.6%
HTML
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README
Yessenov Data Lab 2026
My work from Yessenov Data Lab — a 4-week intensive Machine Learning & Data Science program by the Shakhmardan Yessenov Foundation (Kazakhstan, summer 2026).
Each DayN/ folder is one day of the program: labs, project briefs and my solutions.
Program structure
| Week | Days | Topics | Course materials |
|---|---|---|---|
| 1 | Day1–5 | Python, EDA, first ML models (Titanic regression), RAG mini-app | timurbakibayev/ydl-2026 |
| 2 | Day6–10 | Applied ML: sensor data analysis, regression project, HAR team project, Kaggle-style ensemble pipeline | timurbakibayev/ydl-2026 |
| 3 | Day11–15 | Deep learning: NLP, architectures (CLIP), transformers, multimodal capstone | cillustrisimo/ydl_2026 |
| 4 | Day16–20 | Practical AI engineering: agents from scratch, OpenAI Agents SDK, tools & memory, multi-agent systems, RAG | saedhussain/practical_ai_engineering |
Highlights
- Day15 — capstone: multimodal sarcasm detection (MMSD2.0). Text + image classification
- Day12 — CLIP image search — semantic image search engine. Video demo
- Day13 — RU → EN translator built with transformers. Video demo
- Day9 — full Kaggle pipeline: EDA → baseline → feature engineering → CatBoost / MLP / SVM ensembles.
- Day17 — job search agent built with the OpenAI Agents SDK.
Similar repos
Contributors
rassulz
26 commits
Languages
Jupyter Notebook
94.5%
Python
2.6%
HTML
2.4%