Introduction (Regular Expressions) | NLP-Natural Language Processing in Python for Beginners

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NLP-Natural Language Processing in Python for Beginners

By : AI Sciences

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NLP-Natural Language Processing in Python for Beginners

5 (1)

By: AI Sciences

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Overview of this book

Natural Language Processing (NLP), a subdivision of Artificial Intelligence (AI), is the ability of a computer to understand human language the way it’s spoken and written. Human language is typically referred to as natural language. Humans also have different sensors. For instance, ears perform the function of hearing and eyes perform the function of seeing. Similarly, computers have programs for reading and microphones for collecting audio. Just as the human brain processes an input, a computer program processes a specific input. And during processing, the program converts the input to code that the computer understands. This course, Natural Language Processing (NLP), Theory and Practice in Python, introduces you to the concepts, tools, and techniques of machine learning for text data. You will learn the elementary concepts as well as emerging trends in the field of NLP. You will also learn about the implementation and evaluation of different NLP applications using deep learning methods. Code bundles are available here: https://github.com/PacktPublishing/NLP-Natural-Language-Processing-in-Python-for-Beginners

Introduction

Introduction to the Course

Introduction to the Instructor

Introduction to the Co-Instructor

Course Introduction

Introduction (Regular Expressions)

What is Regular Expression

Why Regular Expression

ELIZA Chatbot

Python Regular Expression Package

Metacharacters (Regular Expressions)

Metacharacters

Metacharacters Bigbrackets Exercise

Meta Characters Bigbrackets Exercise Solution

Metacharacters Bigbrackets Exercise 2

Metacharacters Bigbrackets Exercise 2 - Solution

Metacharacters Cap

Metacharacters Cap Exercise 3

Metacharacters Cap Exercise 3 - Solution

Backslash

Backslash Continued

Backslash Continued - 01

Backslash Squared Brackets Exercise

Backslash Squared Brackets Exercise Solution

Backslash Squared Brackets Exercise - Another Solution

Backslash Exercise

Backslash Exercise Solution and Special Sequences Exercise

Solution and Special Sequences Exercise Solution

Metacharacter Asterisk

Metacharacter Asterisk Exercise

Metacharacter Asterisk Exercise Solution

Metacharacter Asterisk Homework

Metacharacter Asterisk Greedy Matching

Metacharacter Plus and Question Mark

Metacharacter Curly Brackets Exercise

Metacharacter Curly Brackets Exercise Solution

Pattern Objects (Regular Expressions)

Pattern Objects

Pattern Objects Match Method Exercise

Pattern Objects Match Method Exercise Solution

Pattern Objects Match Method Versus Search Method

Pattern Objects Finditer Method

Pattern Objects Finditer Method Exercise Solution

More Metacharacters (Regular Expressions)

Metacharacters Logical Or

Metacharacters Beginning and End Patterns

Metacharacters Parentheses

String Modification (Regular Expressions)

String Modification

Word Tokenizer Using Split Method

Sub Method Exercise

Sub Method Exercise Solution

Words and Tokens (Text Preprocessing)

What is a Word

Definition of Word is Task Dependent

Vocabulary and Corpus

Tokens

Tokenization in Spacy

Sentiment Classification (Text Preprocessing)

Yelp Reviews Classification Mini Project Introduction

Yelp Reviews Classification Mini Project Vocabulary Initialization

Yelp Reviews Classification Mini Project Adding Tokens to Vocabulary

Yelp Reviews Classification Mini Project Look Up Functions in Vocabulary

Yelp Reviews Classification Mini Project Building Vocabulary from Data

Yelp Reviews Classification Mini Project One-Hot Encoding

Yelp Reviews Classification Mini Project One-Hot Encoding Implementation

Yelp Reviews Classification Mini Project Encoding Documents

Yelp Reviews Classification Mini Project Encoding Documents Implementation

Yelp Reviews Classification Mini Project Train Test Splits

Yelp Reviews Classification Mini Project Feature Computation

Yelp Reviews Classification Mini Project Classification

Language Independent Tokenization (Text Preprocessing)

Tokenization in Detial Introduction

Tokenization is Hard

Tokenization Byte Pair Encoding

Tokenization Byte Pair Encoding Example

Tokenization Byte Pair Encoding on Test Data

Tokenization Byte Pair Encoding Implementation Get Pair Counts

Tokenization Byte Pair Encoding Implementation Merge in Corpus

Tokenization Byte Pair Encoding Implementation BFE Training

Tokenization Byte Pair Encoding Implementation BFE Encoding

Tokenization Byte Pair Encoding Implementation BFE Encoding One Pair

Tokenization Byte Pair Encoding Implementation BFE Encoding One Pair 1

Text Normalization(Text Preprocessing)

Word Normalization Case Folding

Word Normalization Lemmatization

Word Normalization Stemming

Word Normalization Sentence Segmentation

String Matching and Spelling Correction (Text Preprocessing)

Spelling Correction Minimum Edit Distance Introduction

Spelling Correction Minimum Edit Distance Example

Spelling Correction Minimum Edit Distance Table Filling

Spelling Correction Minimum Edit Distance Dynamic Programming

Spelling Correction Minimum Edit Distance Pseudocode

Spelling Correction Minimum Edit Distance Implementation

Spelling Correction Minimum Edit Distance Implementation Bug fixing

Spelling Correction Implementation

Language Modeling

What is a Language Model

Language Model Formal Definition

Language Model Curse of Dimensionality

Language Model Markov Assumption and N-Grams

Language Model Implementation Setup

Language Model Implementation N-grams Function

Language Model Implementation Update Counts Function

Language Model Implementation Probability Model Function

Language Model Implementation Reading Corpus

Language Model Implementation Sampling Text

Topic Modelling with Word and Document Representations

One-Hot Vectors

One-Hot Vectors Implementation

One-Hot Vectors Limitations

One-Hot Vectors Used as Target Labeling

Term Frequency for Document Representations

Term Frequency for Document Representations Implementations

Term Frequency for Word Representations

TFIDF for Document Representations

TFIDF for Document Representations Implementation Reading Corpus

TFIDF for Document Representations Implementation Computing Document Frequency

TFIDF for Document Representations Implementation Computing TFIDF

Topic Modeling with TFIDF 1

Topic Modeling with TFIDF 2

Topic Modeling with TFIDF 3

Topic Modeling with TFIDF 4

Topic Modeling with Gensim

Word Embeddings LSI

Word Co-Occurrence Matrix

Word Co-Occurrence Matrix Versus Document-Term Matrix

Word Co-Occurrence Matrix Implementation Preparing Data

Word Co-Occurrence Matrix Implementation Preparing Data 2

Word Co-Occurrence Matrix Implementation Preparing Data Getting Vocabulary

Word Co-Occurrence Matrix Implementation Final Function

Word Co-Occurrence Matrix Implementation Handling Memory Issues on Large Corpora

Word Co-Occurrence Matrix Sparsity

Word Co-Occurrence Matrix Positive Point Wise Mutual Information PPMI

PCA for Dense Embeddings

Latent Semantic Analysis

Latent Semantic Analysis Implementation

Word Semantics

Cosine Similarity

Cosine Similarity Getting Norms of Vectors

Cosine Similarity Normalizing Vectors

Cosine Similarity with More than One Vector

Cosine Similarity Getting Most Similar Words in the Vocabulary

Cosine Similarity Getting Most Similar Words in the Vocabulary Fixing bug

Cosine Similarity Word2Vec Embeddings

Word Analogies

Words Analogies Implementation 1

Word Analogies Implementation 2

Word Visualizations

Word Visualizations Implementation

Word Visualizations Implementation 2

Word2vec(Optional)

Static and Dynamic Embeddings

Self Supervision

Word2Vec Algorithm Abstract

Word2Vec: Why Negative Sampling

Word2Vec: What is Skip Gram

Word2Vec: How to Define Probability Law

Word2Vec Sigmoid

Word2Vec Formalizing Loss Function

Word2Vec Loss Function

Word2Vec Gradient Descent Step

Word2Vec Implementation Preparing Data

Word2Vec Implementation Gradient Step

Word2Vec Implementation Driver Function

Need of Deep Learning for NLP (NLP with Deep Learning DNN)

Why RNNs for NLP

PyTorch Installation and Tensors Introduction

Automatic Differentiation PyTorch

Introduction (NLP with Deep Learning DNN)

Why DNNs in Machine Learning

Representational Power and Data Utilization Capacity of DNN

Perceptron

Perceptron Implementation

DNN Architecture

DNN Forwardstep Implementation

DNN Why Activation Function is Required

DNN Properties of Activation Function

DNN Activation Functions in PyTorch

DNN What is Loss Function

DNN Loss Function in PyTorch

Training (NLP with Deep Learning DNN)

DNN Gradient Descent

DNN Gradient Descent Implementation

DNN Gradient Descent Stochastic Batch Minibatch

DNN Gradient Descent Summary

DNN Implementation Gradient Step

DNN Implementation Stochastic Gradient Descent

DNN Implementation Batch Gradient Descent

DNN Implementation Minibatch Gradient Descent

DNN Implementation in PyTorch

Hyperparameters (NLP with Deep Learning DNN)

DNN Weights Initializations

DNN Learning Rate

DNN Batch Normalization

DNN Batch Normalization Implementation

DNN Optimizations

DNN Dropout

DNN Dropout in PyTorch

DNN Early Stopping

DNN Hyperparameters

DNN PyTorch CIFAR10 Example

Introduction (NLP with Deep Learning RNN)

What is RNN

Understanding RNN with a Simple Example

RNN Applications Human Activity Recognition

RNN Applications Image Captioning

RNN Applications Machine Translation

RNN Applications Speech Recognition Stock Price Prediction

RNN Models

Mini-Project Language Modelling (NLP with Deep Learning RNN)

Language Modeling Next Word Prediction

Language Modeling Next Word Prediction Vocabulary Index

Language Modeling Next Word Prediction Vocabulary Index Embeddings

Language Modeling Next Word Prediction RNN Architecture

Language Modeling Next Word Prediction Python 1

Language Modeling Next Word Prediction Python 2

Language Modeling Next Word Prediction Python 3

Language Modeling Next Word Prediction Python 4

Language Modeling Next Word Prediction Python 5

Language Modeling Next Word Prediction Python 6

Mini-Project Sentiment Classification (NLP with Deep Learning RNN)

Vocabulary Implementation

Vocabulary Implementation Helpers

Vocabulary Implementation From File

Vectorizer

RNN Setup

RNN Setup 1

RNN in PyTorch (NLP with Deep Learning RNN)

RNN In PyTorch Introduction

RNN in PyTorch Embedding Layer

RNN in PyTorch Nn Rnn

RNN in PyTorch Output Shapes

RNN in PyTorch Gated Units

RNN in PyTorch Gated Units GRU LSTM

RNN in PyTorch Bidirectional RNN

RNN in PyTorch Bidirectional RNN Output Shapes

RNN in PyTorch Bidirectional RNN Output Shapes Separation

RNN in PyTorch Example

Advanced RNN Models (NLP with Deep Learning RNN)

RNN Encoder Decoder

RNN Attention

Neural Machine Translation

Introduction to Dataset and Packages

Implementing Language Class

Testing Language Class and Implementing Normalization

Reading Datafile

Reading Building Vocabulary

EncoderRNN

DecoderRNN

DecoderRNN Forward Step

DecoderRNN Helper Functions

Training Module

Stochastic Gradient Descent

NMT Training

NMT Evaluation

NLP-Natural Language Processing in Python for Beginners

By : AI Sciences

NLP-Natural Language Processing in Python for Beginners

By: AI Sciences

Overview of this book

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