| Module Name | Download |
|---|---|
| Week_01_Assignment_1 | Week_01_Assignment_1 |
| Week_02_Assignment_2 | Week_02_Assignment_2 |
| Week_03_Assignment_3 | Week_03_Assignment_3 |
| Week_04_Assignment_4 | Week_04_Assignment_4 |
| Week_05_Assignment_5 | Week_05_Assignment_5 |
| Week_06_Assignment_6 | Week_06_Assignment_6 |
| Week_07_Assignment_7 | Week_07_Assignment_7 |
| Week_08_Assignment_8 | Week_08_Assignment_8 |
| Week_09_Assignment_9 | Week_09_Assignment_9 |
| Week_10_Assignment_10 | Week_10_Assignment_10 |
| Week_11_Assignment_11 | Week_11_Assignment_11 |
| Week_12_Assignment_12 | Week_12_Assignment_12 |
| Sl.No | Chapter Name | MP4 Download |
|---|---|---|
| 1 | Introduction | Download |
| 2 | Operations on a Corpus | Download |
| 3 | Probability and NLP | Download |
| 4 | Vector Space models | Download |
| 5 | Sequence Learning | Download |
| 6 | Machine Translation | Download |
| 7 | Preprocessing | Download |
| 8 | Statistical Properties of Words - Part 01 | Download |
| 9 | Statistical Properties of Words - Part 02 | Download |
| 10 | Statistical Properties of Words - Part 03 | Download |
| 11 | Vector Space Models for NLP | Download |
| 12 | Document Similarity - Demo, Inverted index, Exercise | Download |
| 13 | Vector Representation of words | Download |
| 14 | Contextual understanding of text | Download |
| 15 | Co-occurence matrix, n-grams | Download |
| 16 | Collocations, Dense word Vectors | Download |
| 17 | SVD, Dimensionality reduction, Demo | Download |
| 18 | Query Processing | Download |
| 19 | Topic Modeling | Download |
| 20 | Examples for word prediction | Download |
| 21 | Introduction to Probability in the context of NLP | Download |
| 22 | Joint and conditional probabilities, independence with examples | Download |
| 23 | The definition of probabilistic language model | Download |
| 24 | Chain rule and Markov assumption | Download |
| 25 | Generative Models | Download |
| 26 | Bigram and Trigram Language models -peeking indide the model building | Download |
| 27 | Out of vocabulary words and curse of dimensionality | Download |
| 28 | Exercise | Download |
| 29 | Naive-Bayes, classification | Download |
| 30 | Machine learning, perceptron, linearly separable | Download |
| 31 | Linear Models for Claassification | Download |
| 32 | Biological Neural Network | Download |
| 33 | Perceptron | Download |
| 34 | Perceptron Learning | Download |
| 35 | Logical XOR | Download |
| 36 | Activation Functions | Download |
| 37 | Gradient Descent | Download |
| 38 | Feedforward and Backpropagation Neural Network | Download |
| 39 | Why Word2Vec? | Download |
| 40 | What are CBOW and Skip-Gram Models? | Download |
| 41 | One word learning architecture | Download |
| 42 | Forward pass for Word2Vec | Download |
| 43 | Matrix Operations Explained | Download |
| 44 | CBOW and Skip Gram Models | Download |
| 45 | Building Skip-gram model using Python | Download |
| 46 | Reduction of complexity - sub-sampling, negative sampling | Download |
| 47 | Binay tree, Hierarchical softmax | Download |
| 48 | Mapping the output layer to Softmax | Download |
| 49 | Updating the weights using hierarchical softmax | Download |
| 50 | Discussion on the results obtained from word2vec | Download |
| 51 | Recap and Introduction | Download |
| 52 | ANN as a LM and its limitations | Download |
| 53 | Sequence Learning and its applications | Download |
| 54 | Introuduction to Recurrent Neural Network | Download |
| 55 | Unrolled RNN | Download |
| 56 | RNN - Based Language Model | Download |
| 57 | BPTT - Forward Pass | Download |
| 58 | BPTT - Derivatives for W,V and U | Download |
| 59 | BPTT - Exploding and vanishing gradient | Download |
| 60 | LSTM | Download |
| 61 | Truncated BPTT | Download |
| 62 | GRU | Download |
| 63 | Introduction and Historical Approaches to Machine Translation | Download |
| 64 | What is SMT? | Download |
| 65 | Noisy Channel Model, Bayes Rule, Language Model | Download |
| 66 | Translation Model, Alignment Variables | Download |
| 67 | Alignments again! | Download |
| 68 | IBM Model 1 | Download |
| 69 | IBM Model 2 | Download |
| 70 | Introduction to Phrase-based translation | Download |
| 71 | Symmetrization of alignments | Download |
| 72 | Extraction of Phrases | Download |
| 73 | Learning/estimating the phrase probabilities using another Symmetrization example | Download |
| 74 | Introduction to evaluation of Machine Translation | Download |
| 75 | BLEU - "A short Discussion of the seminal paper" | Download |
| 76 | BLEU Demo using NLTK and other metrics | Download |
| 77 | Encoder-Decoder model for Neural Machine Translation | Download |
| 78 | RNN Based Machine Translation | Download |
| 79 | Recap and Connecting Bloom Taxonomy with Machine Learning | Download |
| 80 | Introduction to Attention based Translation | Download |
| 81 | Research Paper discussion on "Neural machine translation by jointly learning to align and translate" | Download |
| 82 | Typical NMT architecture architecture and models for multi-language translation | Download |
| 83 | Beam Search | Download |
| 84 | Variants of Gradient Descend | Download |
| 85 | Introduction to Conversation Modeling | Download |
| 86 | A few examples in Conversation Modeling | Download |
| 87 | Some ideas to Implement IR-based Conversation Modeling | Download |
| 88 | Discussion of some ideas in Question Answering | Download |
| 89 | Hyperspace Analogue to Language - HAL | Download |
| 90 | Correlated Occurence Analogue to Lexical Semantic - COALS | Download |
| 91 | Global Vectors - Glove | Download |
| 92 | Evaluation of Word vectors | Download |
| Sl.No | Chapter Name | English |
|---|---|---|
| 1 | Introduction | Download Verified |
| 2 | Operations on a Corpus | Download Verified |
| 3 | Probability and NLP | Download Verified |
| 4 | Vector Space models | Download Verified |
| 5 | Sequence Learning | Download Verified |
| 6 | Machine Translation | Download Verified |
| 7 | Preprocessing | Download Verified |
| 8 | Statistical Properties of Words - Part 01 | Download Verified |
| 9 | Statistical Properties of Words - Part 02 | Download Verified |
| 10 | Statistical Properties of Words - Part 03 | Download Verified |
| 11 | Vector Space Models for NLP | Download Verified |
| 12 | Document Similarity - Demo, Inverted index, Exercise | Download Verified |
| 13 | Vector Representation of words | Download Verified |
| 14 | Contextual understanding of text | Download Verified |
| 15 | Co-occurence matrix, n-grams | Download Verified |
| 16 | Collocations, Dense word Vectors | Download Verified |
| 17 | SVD, Dimensionality reduction, Demo | Download Verified |
| 18 | Query Processing | Download Verified |
| 19 | Topic Modeling | Download Verified |
| 20 | Examples for word prediction | Download Verified |
| 21 | Introduction to Probability in the context of NLP | Download Verified |
| 22 | Joint and conditional probabilities, independence with examples | Download Verified |
| 23 | The definition of probabilistic language model | Download Verified |
| 24 | Chain rule and Markov assumption | Download Verified |
| 25 | Generative Models | Download Verified |
| 26 | Bigram and Trigram Language models -peeking indide the model building | Download Verified |
| 27 | Out of vocabulary words and curse of dimensionality | Download Verified |
| 28 | Exercise | Download Verified |
| 29 | Naive-Bayes, classification | Download Verified |
| 30 | Machine learning, perceptron, linearly separable | Download Verified |
| 31 | Linear Models for Claassification | Download Verified |
| 32 | Biological Neural Network | Download Verified |
| 33 | Perceptron | Download Verified |
| 34 | Perceptron Learning | Download Verified |
| 35 | Logical XOR | Download Verified |
| 36 | Activation Functions | Download Verified |
| 37 | Gradient Descent | Download Verified |
| 38 | Feedforward and Backpropagation Neural Network | Download Verified |
| 39 | Why Word2Vec? | Download Verified |
| 40 | What are CBOW and Skip-Gram Models? | Download Verified |
| 41 | One word learning architecture | Download Verified |
| 42 | Forward pass for Word2Vec | Download Verified |
| 43 | Matrix Operations Explained | Download Verified |
| 44 | CBOW and Skip Gram Models | Download Verified |
| 45 | Building Skip-gram model using Python | Download Verified |
| 46 | Reduction of complexity - sub-sampling, negative sampling | Download Verified |
| 47 | Binay tree, Hierarchical softmax | Download Verified |
| 48 | Mapping the output layer to Softmax | Download Verified |
| 49 | Updating the weights using hierarchical softmax | Download Verified |
| 50 | Discussion on the results obtained from word2vec | Download Verified |
| 51 | Recap and Introduction | Download Verified |
| 52 | ANN as a LM and its limitations | Download Verified |
| 53 | Sequence Learning and its applications | Download Verified |
| 54 | Introuduction to Recurrent Neural Network | Download Verified |
| 55 | Unrolled RNN | Download Verified |
| 56 | RNN - Based Language Model | Download Verified |
| 57 | BPTT - Forward Pass | Download Verified |
| 58 | BPTT - Derivatives for W,V and U | Download Verified |
| 59 | BPTT - Exploding and vanishing gradient | Download Verified |
| 60 | LSTM | Download Verified |
| 61 | Truncated BPTT | Download Verified |
| 62 | GRU | Download Verified |
| 63 | Introduction and Historical Approaches to Machine Translation | Download Verified |
| 64 | What is SMT? | Download Verified |
| 65 | Noisy Channel Model, Bayes Rule, Language Model | Download Verified |
| 66 | Translation Model, Alignment Variables | Download Verified |
| 67 | Alignments again! | Download Verified |
| 68 | IBM Model 1 | Download Verified |
| 69 | IBM Model 2 | Download Verified |
| 70 | Introduction to Phrase-based translation | Download Verified |
| 71 | Symmetrization of alignments | Download Verified |
| 72 | Extraction of Phrases | Download Verified |
| 73 | Learning/estimating the phrase probabilities using another Symmetrization example | Download Verified |
| 74 | Introduction to evaluation of Machine Translation | Download Verified |
| 75 | BLEU - "A short Discussion of the seminal paper" | Download Verified |
| 76 | BLEU Demo using NLTK and other metrics | Download Verified |
| 77 | Encoder-Decoder model for Neural Machine Translation | Download Verified |
| 78 | RNN Based Machine Translation | Download Verified |
| 79 | Recap and Connecting Bloom Taxonomy with Machine Learning | Download Verified |
| 80 | Introduction to Attention based Translation | Download Verified |
| 81 | Research Paper discussion on "Neural machine translation by jointly learning to align and translate" | Download Verified |
| 82 | Typical NMT architecture architecture and models for multi-language translation | Download Verified |
| 83 | Beam Search | Download Verified |
| 84 | Variants of Gradient Descend | Download Verified |
| 85 | Introduction to Conversation Modeling | Download Verified |
| 86 | A few examples in Conversation Modeling | Download Verified |
| 87 | Some ideas to Implement IR-based Conversation Modeling | Download Verified |
| 88 | Discussion of some ideas in Question Answering | Download Verified |
| 89 | Hyperspace Analogue to Language - HAL | Download Verified |
| 90 | Correlated Occurence Analogue to Lexical Semantic - COALS | Download Verified |
| 91 | Global Vectors - Glove | Download Verified |
| 92 | Evaluation of Word vectors | Download Verified |
| Sl.No | Language | Book link |
|---|---|---|
| 1 | English | Download |
| 2 | Bengali | Not Available |
| 3 | Gujarati | Not Available |
| 4 | Hindi | Not Available |
| 5 | Kannada | Not Available |
| 6 | Malayalam | Not Available |
| 7 | Marathi | Not Available |
| 8 | Tamil | Not Available |
| 9 | Telugu | Not Available |