Natural Language Processing

Natural Language Processing (NLP) - from Tokenization, Embeddings, Transformers to LLMs
Playlist Natural Language Processing | Full Course

Chapters

  1. 01
    Introduction

    Introduction to Natural Language Processing

    3 min read
  2. 02
    Text Pre-Processing

    Text Pre-Processing - Cleaning, Stemming & Lemmatization

    2 min read
  3. 03
    Tokenization

    Tokenization - Byte Pair Encoding, WordPiece & SentencePiece

    5 min read
  4. 04
    Text Embedding

    Text Embeddings - OHE, BoW, TF-IDF, Word2Vec, GloVe & FastText

    10 min read
  5. 05
    RNN

    Recurrent Neural Network

    7 min read
  6. 06
    LSTM

    Long Short Term Memory

    4 min read
  7. 07
    GRU

    Gated Recurrent Unit

    5 min read
  8. 08
    Attention

    Attention Mechanism (Bahdanau Attention)

    4 min read
  9. 09
    Self Attention

    Self Attention - Transformer Architecture

    4 min read
  10. 10
    Transformer

    Transformer Architecture - Attention Is All You Need !

    6 min read
  11. 11
    LLM

    Large Language Model

    8 min read
  12. 12
    BERT

    Bidirectional Encoder Representations from Transformers

    4 min read

This course includes

12 articles
1h 2m reading time
23 videos • 9 hr 57 mins

Course content

12 sections • 93 topics • Read: 1h 2m • Video: 9 hr 57 mins

Introduction 3 Topics, Read: 3 mins, 1 Video: 31 mins
Natural Language Processing
Corpus to Model
Evolution of LLM
Evolution of LLMs | From RNN to Transformer | Natural Language Processing (NLP) Watch 31 mins
Text Pre-Processing 4 Topics, Read: 2 mins, 1 Video: 10 mins
Text Pre-Processing
Cleaning
Stemming
Lemmatization
Text Pre Processing for LLM | Text Cleaning | Stemming | Lemmatization Watch 10 mins
Tokenization 7 Topics, Read: 5 mins, 1 Video: 32 mins
Tokenization
Word-Level Tokenization
Character-Level Tokenization
Sub-Word Tokenization
Byte Pair Encoding
WordPiece
SentencePiece
What are Tokens in LLM ? | How tokenization works ? | Byte Pair Encoding | Detailed Explanation Watch 32 mins
Text Embedding 13 Topics, Read: 10 mins, 4 Videos: 1 hr 49 mins
Text Embedding
One Hot Encoding
Bag of Words
Term Frequency-Inverse Document Frequency (TF-IDF)
Distributed Text Representation
Word2Vec
Skip-Gram
Negative Sampling
How Negative Sampling Works ?
Global Vectors (GloVe)
Comparison: GloVe Vs Word2Vec
FastText
Comparison: FastText Vs GloVe Vs Word2Vec
Word Embeddings (Vector) | OHE | Bag of Words | Term Frequency Inverse Document Frequency (TFIDF) Watch 29 mins
Word2Vec Embedding | Detailed Explanation with Maths | Skip Gram | CBOW | Negative Sampling Watch 32 mins
Global Vectors (GloVe) Embedding | Detailed Explanation | Matrix Factorization | Word2Vec Vs GloVe Watch 27 mins
FastText Embedding for Rare (OOV) Words | Explained with Example | FastText Vs GloVe Vs Word2Vec Watch 20 mins
RNN 7 Topics, Read: 7 mins, 3 Videos: 1 hr 20 mins
N-Gram Model
Recurrent Neural Network(RNN)
Back Propagation Through Time (BPTT)
Vanishing Gradient Problem
Exploding Gradient Problem
Applications of RNN
RNN Variants
Recurrent Neural Network (RNN) Architecture | Teacher Forcing | Detailed Explanation with Maths Watch 34 mins
Back Propagation Through Time (BPTT) in RNN | Vanishing Gradient | Exploding Gradient | Explained Watch 29 mins
Applications Of RNN | Text Generation | Sentiment Analysis | Machine Translation | Bi-RNN Watch 17 mins
LSTM 8 Topics, Read: 4 mins, 1 Video: 24 mins
RNN Limitation
Long Short Term Memory (LSTM)
Forget Gate
Input Gate & Candidates
Output Gate
Back Propagation Through Time
Constant Error Carousel
Long Short Term Memory (LSTM) | Forget, Input & Output Gate | Constant Error Carousel | Explained Watch 24 mins
GRU 9 Topics, Read: 5 mins, 1 Video: 26 mins
Issue with LSTM
Gated Recurrent Unit (GRU)
Reset Gate
Candidate Hidden State
Update Gate
Back Propagation Through Time
Constant Error Carousel
How GRU Works?
Gated Recurrent Unit (GRU) | Reset & Update Gate | Constant Error Carousel | Detailed Explanation Watch 26 mins
Attention 5 Topics, Read: 4 mins, 1 Video: 35 mins
Issue with Encoder-Decoder RNNs
Attention Mechanism
Query, Key & Value
Bahdanau Attention
Dot Product Attention
Attention Mechanism | Query, Key & Value | Bahdanau Attention | Detailed Explanation with Maths Watch 35 mins
Self Attention 5 Topics, Read: 4 mins, 1 Video: 31 mins
Issue with RNN based Architecture
Attention Is All You Need !
Need For Self-Attention
Self-Attention
Self-Attention Query, Key & Value
Self Attention in Transformer Architecture | Query, Key & Value | Detailed Explanation with Example Watch 31 mins
Transformer 14 Topics, Read: 6 mins, 3 Videos: 1 hr 22 mins
Transformer
Attention Is All You Need
Self Attention
Limitations of Single Head Self Attention
Multi-Head Attention
Masked Multi-Head Attention
Encoder-Decoder Attention
Feed Forward Network
Residual Connection
Layer Normalization
Positional Encoding
Rotary Positional Embeddings (RoPE)
Attention with Linear Biases (ALiBi)
Multi Head Self Attention in Transformer Architecture | Detailed Explanation Watch 13 mins
Positional Encoding in Transformers | RoPE | ALiBi | Detailed Explanation with Maths Watch 18 mins
Transformer Architecture | Attention Is All You Need | Detailed Explanation with Maths Watch 49 mins
LLM 11 Topics, Read: 8 mins, 4 Videos: 1 hr 38 mins
Transformer Variants
LLM Training Phases
Pre-Training
Transfer Learning
Supervised Fine-Tuning (SFT)
Chain of Thought
Tool/Function Calling
Limitations of SFT
Reinforcement Learning from Human Feedback (RLHF)
Direct Preference Optimization (DPO)
Parameter-Efficient Fine-Tuning (PEFT)
Supervised Fine Tuning (SFT) | Chain of Thought | Tool/Function Calling | Detailed Explanation Watch 22 mins
Reinforcement Learning From Human Feedback (RLHF) | Direct Preference Optimization (DPO) | Explained Watch 18 mins
Performance Efficient Fine Tuning (PEFT) | Low Rank Adaptation (LoRA) | Detailed Explanation Watch 22 mins
How Large Language Models (LLMs) are Trained ? | Pre-Training | Supervised Fine Tuning (SFT) | RLHF Watch 35 mins
BERT 7 Topics, Read: 4 mins, 2 Videos: 34 mins
Bidirectional Encoder Representations from Transformers (BERT)
Masked Language Modeling
Next Sentence Prediction
Special Tokens
Key Applications of BERT
Limitation of BERT
Sentence BERT
Bidirectional Encoder Representations from Transformers (BERT) | Masked Language Modeling |Explained Watch 22 mins
Sentence BERT (SBERT) | Siamese Network | Pooling Strategy | Detailed Explanation Watch 11 mins