Introduction to Natural Language Processing: notebooks and data for the CourseLabs course, runnable in Google Colab. Course material CC BY 4.0.
Jupyter Notebook
0
1 commits
updated Sep 25, 2026
The notebooks of the CourseLabs course Natural Language Processing, ready to
run in Google Colab. Each lab is a folder; the shared data is in data/.
Click a badge to open a notebook in Colab, then run its first code cell. That
cell clones this repository, moves into the lab's folder, links data/,
installs the few packages Colab lacks and downloads the NLTK data, then prints
one line saying it is ready. Models download from Hugging Face as the notebook
first uses them. In a CourseLabs session the same cell does nothing, because
everything is already installed there.
To work on your own computer instead, download a lab's zip (the folder with its
data) or all the data, install the lab's
requirements.txt, and open the notebooks in Jupyter.
The checks in each notebook run anywhere. The one in Lab 11 that scores your fine-tuned model against held-out answers runs only in CourseLabs, and so do the checkpoint and the sign-off.
Folder: lab-nlp-01-why-cant-a-computer-read/. Download: lab-nlp-01-why-cant-a-computer-read.zip (the folder with its data).
01_01_Tokens.ipynb 01_02_Normalising_Words.ipynb 01_03_Tags_and_Entities.ipynb 01_04_On_Your_Own.ipynbCredits: based on Chapter 1 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; HuggingFaceTB/SmolLM2-360M-Instruct; google-bert/bert-base-uncased.
Folder: lab-nlp-02-turning-words-into-numbers/. Download: lab-nlp-02-turning-words-into-numbers.zip (the folder with its data).
02_01_Bag_of_Words.ipynb 02_02_TF_IDF.ipynb 02_03_Similarity_and_Search.ipynb 02_04_On_Your_Own.ipynbCredits: based on Chapter 2 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; SMS Spam Collection, Almeida and Gomez Hidalgo, UCI, CC BY 4.0, https://archive.ics.uci.edu/dataset/228/sms+spam+collection; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-03-teaching-a-machine-what-spam-looks-like/. Download: lab-nlp-03-teaching-a-machine-what-spam-looks-like.zip (the folder with its data).
03_01_Spam_and_the_Baseline.ipynb 03_02_Logistic_Regression.ipynb 03_03_Support_Vector_Machines.ipynb 03_04_On_Your_Own.ipynbCredits: based on Chapter 3 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; SMS Spam Collection, Almeida and Gomez Hidalgo, UCI, CC BY 4.0, https://archive.ics.uci.edu/dataset/228/sms+spam+collection; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-04-which-classifier-and-why/. Download: lab-nlp-04-which-classifier-and-why.zip (the folder with its data).
04_01_Nearest_Neighbours.ipynb 04_02_Naive_Bayes.ipynb 04_03_Choosing_a_Classifier.ipynb 04_04_On_Your_Own.ipynbCredits: based on Chapter 4 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; UCI Sentiment Labelled Sentences, Kotzias et al. (2015), CC BY 4.0, https://archive.ics.uci.edu/dataset/331/sentiment+labelled+sentences; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-05-words-as-points-in-space/. Download: lab-nlp-05-words-as-points-in-space.zip (the folder with its data).
05_01_Pretrained_Word_Vectors.ipynb 05_02_Skip_Gram_in_PyTorch.ipynb 05_03_Products_as_Words.ipynb 05_04_On_Your_Own.ipynbCredits: based on Chapter 5 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; UCI Online Retail, Daqing Chen (2015), CC BY 4.0, https://archive.ics.uci.edu/dataset/352/online+retail; GloVe 6B 50d, Pennington, Socher and Manning (2014), PDDL 1.0, https://nlp.stanford.edu/projects/glove/.
Folder: lab-nlp-06-a-neuron-from-scratch/. Download: lab-nlp-06-a-neuron-from-scratch.zip (the folder with its data).
06_01_One_Neuron.ipynb 06_02_XOR_and_Hidden_Layers.ipynb 06_03_Activations_and_Loss.ipynb 06_04_On_Your_Own.ipynbCredits: based on Chapter 6 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-07-how-a-network-learns/. Download: lab-nlp-07-how-a-network-learns.zip (the folder with its data).
07_01_Backprop_by_Hand.ipynb 07_02_Optimisers_Raced.ipynb 07_03_A_Recurrent_Network.ipynb 07_04_On_Your_Own.ipynbCredits: based on Chapter 7 of Dr. Ernesto Lee's NLP book; Reuters-21578 ApteMod, downloaded by NLTK, CC BY 4.0, https://archive.ics.uci.edu/dataset/137/reuters+21578+text+categorization+collection.
Folder: lab-nlp-08-remembering-across-a-sentence/. Download: lab-nlp-08-remembering-across-a-sentence.zip (the folder with its data).
08_01_Inside_an_LSTM_Cell.ipynb 08_02_LSTM_against_the_RNN.ipynb 08_03_Reading_Both_Ways.ipynb 08_04_On_Your_Own.ipynbCredits: based on Chapter 8 of Dr. Ernesto Lee's NLP book; UCI News Aggregator, Gasparetti (2016), CC BY 4.0, https://archive.ics.uci.edu/dataset/359/news+aggregator.
Folder: lab-nlp-09-from-one-language-to-another/. Download: lab-nlp-09-from-one-language-to-another.zip (the folder with its data).
09_01_Encoder_and_Decoder.ipynb 09_02_Greedy_and_Beam.ipynb 09_03_The_Bottleneck.ipynb 09_04_On_Your_Own.ipynbCredits: based on Chapter 9 of Dr. Ernesto Lee's NLP book; English-Spanish pairs from the Tatoeba Project, CC BY 2.0 FR, https://tatoeba.org, as packaged by https://www.manythings.org/anki/.
Folder: lab-nlp-10-attention-is-the-whole-trick/. Download: lab-nlp-10-attention-is-the-whole-trick.zip (the folder with its data).
10_01_Attention_by_Hand.ipynb 10_02_A_Transformer_Block.ipynb 10_03_What_BERT_Looks_At.ipynb 10_04_On_Your_Own.ipynbCredits: based on Chapter 10 of Dr. Ernesto Lee's NLP book; UCI News Aggregator, Gasparetti (2016), CC BY 4.0, https://archive.ics.uci.edu/dataset/359/news+aggregator; google/bert_uncased_L-4_H-256_A-4.
Folder: lab-nlp-11-bert-and-what-came-after/. Download: lab-nlp-11-bert-and-what-came-after.zip (the folder with its data).
11_01_Masked_Language_Modelling.ipynb 11_02_Fine_Tuning_BERT.ipynb 11_03_Question_Answering.ipynb 11_04_On_Your_Own.ipynbCredits: based on Chapter 11 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; distilbert/distilbert-base-uncased-distilled-squad; google/bert_uncased_L-2_H-128_A-2; google/bert_uncased_L-4_H-256_A-4.
Folder: lab-nlp-12-large-and-small-language-models/. Download: lab-nlp-12-large-and-small-language-models.zip (the folder with its data).
12_01_Next_Token.ipynb 12_02_Instructions_and_Prompts.ipynb 12_03_Retrieval_and_Grounding.ipynb 12_04_On_Your_Own.ipynbCredits: written for CourseLabs; Kittiwake Mobile data, invented for the course; HuggingFaceTB/SmolLM2-360M-Instruct; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-13-models-and-a-database-in-the-browser/. Download: lab-nlp-13-models-and-a-database-in-the-browser.zip (the folder with its data).
README.md to run it from a local static server.Credits: written for CourseLabs.
See LICENSE.md: the course material is CC BY 4.0, and the data keeps its original licences, with a link to each original.
Introduction to Natural Language Processing: notebooks and data for the CourseLabs course, runnable in Google Colab. Course material CC BY 4.0.
Jupyter Notebook
0
1 commits
updated Sep 25, 2026
The notebooks of the CourseLabs course Natural Language Processing, ready to
run in Google Colab. Each lab is a folder; the shared data is in data/.
Click a badge to open a notebook in Colab, then run its first code cell. That
cell clones this repository, moves into the lab's folder, links data/,
installs the few packages Colab lacks and downloads the NLTK data, then prints
one line saying it is ready. Models download from Hugging Face as the notebook
first uses them. In a CourseLabs session the same cell does nothing, because
everything is already installed there.
To work on your own computer instead, download a lab's zip (the folder with its
data) or all the data, install the lab's
requirements.txt, and open the notebooks in Jupyter.
The checks in each notebook run anywhere. The one in Lab 11 that scores your fine-tuned model against held-out answers runs only in CourseLabs, and so do the checkpoint and the sign-off.
Folder: lab-nlp-01-why-cant-a-computer-read/. Download: lab-nlp-01-why-cant-a-computer-read.zip (the folder with its data).
01_01_Tokens.ipynb 01_02_Normalising_Words.ipynb 01_03_Tags_and_Entities.ipynb 01_04_On_Your_Own.ipynbCredits: based on Chapter 1 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; HuggingFaceTB/SmolLM2-360M-Instruct; google-bert/bert-base-uncased.
Folder: lab-nlp-02-turning-words-into-numbers/. Download: lab-nlp-02-turning-words-into-numbers.zip (the folder with its data).
02_01_Bag_of_Words.ipynb 02_02_TF_IDF.ipynb 02_03_Similarity_and_Search.ipynb 02_04_On_Your_Own.ipynbCredits: based on Chapter 2 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; SMS Spam Collection, Almeida and Gomez Hidalgo, UCI, CC BY 4.0, https://archive.ics.uci.edu/dataset/228/sms+spam+collection; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-03-teaching-a-machine-what-spam-looks-like/. Download: lab-nlp-03-teaching-a-machine-what-spam-looks-like.zip (the folder with its data).
03_01_Spam_and_the_Baseline.ipynb 03_02_Logistic_Regression.ipynb 03_03_Support_Vector_Machines.ipynb 03_04_On_Your_Own.ipynbCredits: based on Chapter 3 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; SMS Spam Collection, Almeida and Gomez Hidalgo, UCI, CC BY 4.0, https://archive.ics.uci.edu/dataset/228/sms+spam+collection; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-04-which-classifier-and-why/. Download: lab-nlp-04-which-classifier-and-why.zip (the folder with its data).
04_01_Nearest_Neighbours.ipynb 04_02_Naive_Bayes.ipynb 04_03_Choosing_a_Classifier.ipynb 04_04_On_Your_Own.ipynbCredits: based on Chapter 4 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; UCI Sentiment Labelled Sentences, Kotzias et al. (2015), CC BY 4.0, https://archive.ics.uci.edu/dataset/331/sentiment+labelled+sentences; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-05-words-as-points-in-space/. Download: lab-nlp-05-words-as-points-in-space.zip (the folder with its data).
05_01_Pretrained_Word_Vectors.ipynb 05_02_Skip_Gram_in_PyTorch.ipynb 05_03_Products_as_Words.ipynb 05_04_On_Your_Own.ipynbCredits: based on Chapter 5 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; UCI Online Retail, Daqing Chen (2015), CC BY 4.0, https://archive.ics.uci.edu/dataset/352/online+retail; GloVe 6B 50d, Pennington, Socher and Manning (2014), PDDL 1.0, https://nlp.stanford.edu/projects/glove/.
Folder: lab-nlp-06-a-neuron-from-scratch/. Download: lab-nlp-06-a-neuron-from-scratch.zip (the folder with its data).
06_01_One_Neuron.ipynb 06_02_XOR_and_Hidden_Layers.ipynb 06_03_Activations_and_Loss.ipynb 06_04_On_Your_Own.ipynbCredits: based on Chapter 6 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-07-how-a-network-learns/. Download: lab-nlp-07-how-a-network-learns.zip (the folder with its data).
07_01_Backprop_by_Hand.ipynb 07_02_Optimisers_Raced.ipynb 07_03_A_Recurrent_Network.ipynb 07_04_On_Your_Own.ipynbCredits: based on Chapter 7 of Dr. Ernesto Lee's NLP book; Reuters-21578 ApteMod, downloaded by NLTK, CC BY 4.0, https://archive.ics.uci.edu/dataset/137/reuters+21578+text+categorization+collection.
Folder: lab-nlp-08-remembering-across-a-sentence/. Download: lab-nlp-08-remembering-across-a-sentence.zip (the folder with its data).
08_01_Inside_an_LSTM_Cell.ipynb 08_02_LSTM_against_the_RNN.ipynb 08_03_Reading_Both_Ways.ipynb 08_04_On_Your_Own.ipynbCredits: based on Chapter 8 of Dr. Ernesto Lee's NLP book; UCI News Aggregator, Gasparetti (2016), CC BY 4.0, https://archive.ics.uci.edu/dataset/359/news+aggregator.
Folder: lab-nlp-09-from-one-language-to-another/. Download: lab-nlp-09-from-one-language-to-another.zip (the folder with its data).
09_01_Encoder_and_Decoder.ipynb 09_02_Greedy_and_Beam.ipynb 09_03_The_Bottleneck.ipynb 09_04_On_Your_Own.ipynbCredits: based on Chapter 9 of Dr. Ernesto Lee's NLP book; English-Spanish pairs from the Tatoeba Project, CC BY 2.0 FR, https://tatoeba.org, as packaged by https://www.manythings.org/anki/.
Folder: lab-nlp-10-attention-is-the-whole-trick/. Download: lab-nlp-10-attention-is-the-whole-trick.zip (the folder with its data).
10_01_Attention_by_Hand.ipynb 10_02_A_Transformer_Block.ipynb 10_03_What_BERT_Looks_At.ipynb 10_04_On_Your_Own.ipynbCredits: based on Chapter 10 of Dr. Ernesto Lee's NLP book; UCI News Aggregator, Gasparetti (2016), CC BY 4.0, https://archive.ics.uci.edu/dataset/359/news+aggregator; google/bert_uncased_L-4_H-256_A-4.
Folder: lab-nlp-11-bert-and-what-came-after/. Download: lab-nlp-11-bert-and-what-came-after.zip (the folder with its data).
11_01_Masked_Language_Modelling.ipynb 11_02_Fine_Tuning_BERT.ipynb 11_03_Question_Answering.ipynb 11_04_On_Your_Own.ipynbCredits: based on Chapter 11 of Dr. Ernesto Lee's NLP book; Kittiwake Mobile data, invented for the course; distilbert/distilbert-base-uncased-distilled-squad; google/bert_uncased_L-2_H-128_A-2; google/bert_uncased_L-4_H-256_A-4.
Folder: lab-nlp-12-large-and-small-language-models/. Download: lab-nlp-12-large-and-small-language-models.zip (the folder with its data).
12_01_Next_Token.ipynb 12_02_Instructions_and_Prompts.ipynb 12_03_Retrieval_and_Grounding.ipynb 12_04_On_Your_Own.ipynbCredits: written for CourseLabs; Kittiwake Mobile data, invented for the course; HuggingFaceTB/SmolLM2-360M-Instruct; ibm-granite/granite-embedding-small-english-r2.
Folder: lab-nlp-13-models-and-a-database-in-the-browser/. Download: lab-nlp-13-models-and-a-database-in-the-browser.zip (the folder with its data).
README.md to run it from a local static server.Credits: written for CourseLabs.
See LICENSE.md: the course material is CC BY 4.0, and the data keeps its original licences, with a link to each original.