Natural Language Processing specialization

Notes, Assignments and Relevant stuff from NLP course by deeplearning.ai, hosted on Coursera.

Course 1: Natural Language Processing with Classification and Vector Spaces

Week 1: Sentiment Analysis with Logistic Regression

• Natural Language Preprocessing
• Visualizing Word Frequencies
• Visualizing Tweets and Logistic Regression models
• Assignment 1

Week 2: Sentiment Analysis with Naive Bayes

• Visualizing likelihoods and confidence ellipses
• Assignment 2

Week 3: Vector Space Models

• Linear algebra in Python with Numpy
• Manipulating word embeddings
• Another explanation about PCA
• Assignment 3

Week 4: Machine Translation and Document Search

• Rotation matrices in L2
• Hash tables
• Assignment 4

Course 2: Natural Language Processing with Probabilistic Models

Week 1: Autocorrect

• Building the vocabulary
• Candidates from edits
• Assignment 1

Week 2: Part of Speech Tagging and Hidden Markov Models

• Parts-of-Speech Tagging - First Steps: Working with text files, Creating a Vocabulary and Handling Unknown Words
• Parts-of-Speech Tagging - Working with tags and Numpy
• Assignment 2

Week 3: Autocomplete and Language Models

• N-grams Corpus preprocessing
• Building the language model
• Out of vocabulary words (OOV)
• Assignment 3

Week 4: Word embeddings with Neural Networks

• Word Embeddings: Ungraded Practice Notebook
• Word Embeddings First Steps: Data Preparation
• Word Embeddings: Intro to CBOW model, activation functions and working with Numpy
• Word Embeddings: Training the CBOW model
• Word Embeddings: Hands On
• Assignment 4

Course 3: Natural Language Processing with Sequence Models

Week 1: Neural Network for Sentiment Analysis

• Introduction to Trax
• Classes and Subclasses
• Data Generators
• Assignment 1

Week 2: Recurrent Neural Networks for Language Modeling

• Hidden State Activation
• Working with JAX NumPy and Calculating Perplexity
• Vanilla RNNs, GRUs and the scan function
• Creating a GRU model using Trax
• Assignment 2

Week 3: LSTM and Name Entity Recognition

• Vanishing Gradient
• Assignment 3

Week 4: Siamese Networks

• Creating a Siamese Model using Trax
• Modified Triplet Loss
• Assignment 4

Course 4: Natural Language Processing with Attention Models

Week 1: Neural Machine Translation

• Stack Semantics
• BLEU score
• Assignment 1

Week 2: Text Summarization

• Attention
• The Transformer Decoder
• Assignment 2

Week 3: Question Answering

• SentencePiece and BPE
• Assignment 3

Week 4: Chatbot

• Reformer LSH
• Revnet
• Assignment 4