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NLP-Natural Language Processing in Python for Beginners
NLP-Natural Language Processing in Python for Beginners

NLP-Natural Language Processing in Python for Beginners: Learn Natural Language Processing Using Spacy, NLTK, PyTorch, Text Preprocessing, Embeddings, Word2Vec, and Deep Learning

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$32.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Aug 2021 23hrs 31mins 1st Edition
Video
$32.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon AI Sciences
Arrow right icon
$32.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Aug 2021 23hrs 31mins 1st Edition
Video
$32.99
Subscription
Free Trial
Renews at $19.99p/m
Video
$32.99
Subscription
Free Trial
Renews at $19.99p/m

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Key benefits

  • Apply the concepts to any language to build customized NLP models
  • Learn machine learning concepts in a more practical way
  • Build your own applications for automatic text generation and language translators

Description

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

Who is this book for?

This course is for complete beginners who are new to NLP, people who want to upgrade their Python programming skills for NLP, and individuals who are passionate about numbers and programming such as data scientists, data analysts, and machine learning practitioners.

What you will learn

  • Learn the fundamentals of NLP using datasets
  • Explore language models and their uses in speech recognition
  • Learn to use software tools such as SpaCY, NLTK, Gensim, and PyTorch
  • Learn the concepts of deep learning theory
  • Explore linear subspaces for word embeddings
  • Understand the architecture of neural networks

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 27, 2021
Length: 23hrs 31mins
Edition : 1st
Language : English
ISBN-13 : 9781803249193
Category :
Languages :
Concepts :
Tools :

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Aug 27, 2021
Length: 23hrs 31mins
Edition : 1st
Language : English
ISBN-13 : 9781803249193
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Total $ 136.97
NLP-Natural Language Processing in Python for Beginners
$32.99
Python Natural Language Processing Cookbook
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Mastering spaCy
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Total $ 136.97 Stars icon

Table of Contents

26 Chapters
Introduction Chevron down icon Chevron up icon
Introduction (Regular Expressions) Chevron down icon Chevron up icon
Metacharacters (Regular Expressions) Chevron down icon Chevron up icon
Pattern Objects (Regular Expressions) Chevron down icon Chevron up icon
More Metacharacters (Regular Expressions) Chevron down icon Chevron up icon
String Modification (Regular Expressions) Chevron down icon Chevron up icon
Words and Tokens (Text Preprocessing) Chevron down icon Chevron up icon
Sentiment Classification (Text Preprocessing) Chevron down icon Chevron up icon
Language Independent Tokenization (Text Preprocessing) Chevron down icon Chevron up icon
Text Normalization(Text Preprocessing) Chevron down icon Chevron up icon
String Matching and Spelling Correction (Text Preprocessing) Chevron down icon Chevron up icon
Language Modeling Chevron down icon Chevron up icon
Topic Modelling with Word and Document Representations Chevron down icon Chevron up icon
Word Embeddings LSI Chevron down icon Chevron up icon
Word Semantics Chevron down icon Chevron up icon
Word2vec(Optional) Chevron down icon Chevron up icon
Need of Deep Learning for NLP (NLP with Deep Learning DNN) Chevron down icon Chevron up icon
Introduction (NLP with Deep Learning DNN) Chevron down icon Chevron up icon
Training (NLP with Deep Learning DNN) Chevron down icon Chevron up icon
Hyperparameters (NLP with Deep Learning DNN) Chevron down icon Chevron up icon
Introduction (NLP with Deep Learning RNN) Chevron down icon Chevron up icon
Mini-Project Language Modelling (NLP with Deep Learning RNN) Chevron down icon Chevron up icon
Mini-Project Sentiment Classification (NLP with Deep Learning RNN) Chevron down icon Chevron up icon
RNN in PyTorch (NLP with Deep Learning RNN) Chevron down icon Chevron up icon
Advanced RNN Models (NLP with Deep Learning RNN) Chevron down icon Chevron up icon
Neural Machine Translation Chevron down icon Chevron up icon

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