NLP/NLU Specialization Notes
Natural Language Processing/Understanding Notes, Resources
Natural Language Processing With Attention Models
NLP With Attention Models
Natural Language Processing With Attention Models Notebooks
Assignment 1: Neural Machine Translation
Basic Attention Operation: Ungraded Lab
Calculating the Bilingual Evaluation Understudy (BLEU) score: Ungraded Lab
Scaled Dot-Product Attention: Ungraded Lab
Assignment 2: Transformer Summarizer
The Three Ways of Attention and Dot Product Attention: Ungraded Lab Notebook
Masking
Positional Encoding
Assignment 3: Question Answering
Assignment 3: Question Answering
Question Answering with BERT and HuggingFace
Question Answering with BERT and HuggingFace 🤗 (Fine-tuning)
SentencePiece and BPE
Natural Language Processing With Classification And Vector Spaces
NLP With Classification and Vector Spaces
Natural Language Processing With Sequence Models
NLP With Sequence Models
Natural Language Processing with Classification and Vector Spaces Notebooks
Assignment 1: Logistic Regression
Preprocessing
Building and Visualizing word frequencies
Visualizing tweets and the Logistic Regression model
Assignment 2: Naive Bayes
Assignment 3: Hello Vectors
Linear algebra in Python with NumPy
Manipulating word embeddings
Another explanation about PCA
Assignment 4 - Naive Machine Translation and LSH
Vector manipulation in Python
Hash functions and multiplanes
Natural Language Processing with Probabilistic Models
NLP With Probabilistic Models
Natural Language Processing with Probabilistic Models Notebooks
Assignment 1: Autocorrect
NLP Course 2 Week 1 Lesson : Building The Model - Lecture Exercise 01
NLP Course 2 Week 1 Lesson : Building The Model - Lecture Exercise 02
Assignment 2: Parts-of-Speech Tagging (POS)
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 3: Language Models: Auto-Complete
N-grams Corpus preprocessing
Building the language model
Out of vocabulary words (OOV)
Assignment 4: Word Embeddings
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
Word Embeddings: Ungraded Practice Notebook
Natural Language Processing with Sequence Models Notebooks
Assignment 1: Deep N-grams
Hidden State Activation : Ungraded Lecture Notebook
Assignment 1: Sentiment with Deep Neural Networks
Vanilla RNNs and GRUs
Lab 1: TensorFlow Tutorial and Some Useful Functions
Calculating perplexity using numpy: Ungraded Lecture Notebook
Assignment 2 - Named Entity Recognition (NER)
Vanishing Gradients and Exploding Gradients in RNNs : Ungraded Lecture Notebook
Evaluate a Siamese model: Ungraded Lecture Notebook
Assignment 3: Question duplicates
Modified Triplet Loss : Ungraded Lecture Notebook
Creating a Siamese model: Ungraded Lecture Notebook
Stanford
Stanford CS 224U,224N
Udacity
NLP Nanodegree
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