NLP – Natural Language Processing with Python

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About Course

Free NLP – Natural Language Processing with Python Course

Looking to master Natural Language Processing (NLP) with Python? This comprehensive course, completely free of charge, is your gateway to becoming an NLP expert.

Offered through Theetay, this course combines the best of Udemy, Udacity, Coursera, MasterClass, NearPeer, and other top platforms, delivering high-quality learning experiences without any cost.

Dive into the world of NLP with Python, starting with the fundamentals. Learn to handle text and PDF files, utilize regular expressions, and explore the power of libraries like NLTK and Spacy for tokenization, parsing, entity recognition, and lemmatization.

Delve deeper into NLP concepts like stemming, lemmatization, stop words, phrase matching, and tokenization. This course also covers essential techniques like Part-of-Speech tagging, enabling your scripts to identify nouns, verbs, and adjectives automatically. Master Named Entity Recognition, allowing your code to recognize entities like money, time, companies, and products within text data.

Visualize these relationships in real-time with state-of-the-art libraries, and discover machine learning with Scikit-Learn for text classification. Build machine learning models to classify movie reviews, detect spam, and explore the world of unsupervised learning methods like topic modeling.

This course doesn’t stop there! Learn advanced topics like sentiment analysis with NLTK and create semantic word vectors with the Word2Vec algorithm. You’ll even explore how to build chatbots using deep learning!

Beyond technical content, this course offers a dedicated Question and Answer forum and a live student chat channel to connect with fellow learners and seek help from instructors. Start your NLP journey today – it’s completely free!

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What Will You Learn?

  • Learn to work with Text Files with Python
  • Learn how to work with PDF files in Python
  • Utilize Regular Expressions for pattern searching in text
  • Use Spacy for ultra fast tokenization
  • Learn about Stemming and Lemmatization
  • Understand Vocabulary Matching with Spacy
  • Use Part of Speech Tagging to automatically process raw text files
  • Understand Named Entity Recognition
  • Visualize POS and NER with Spacy
  • Use SciKit-Learn for Text Classification
  • Use Latent Dirichlet Allocation for Topic Modelling
  • Learn about Non-negative Matrix Factorization
  • Use the Word2Vec algorithm
  • Use NLTK for Sentiment Analysis
  • Use Deep Learning to build out your own chat bot

Course Content

Introduction

  • A Message from the Professor
  • Course Overview – DO NOT SKIP THIS LECTURE PLEASE. IMPORTANT INFO HERE!
    04:07
  • Curriculum Overview
    03:07
  • Installation and Setup Lecture
    11:51
  • Course Material Download Link
    00:00

Python Text Basics

Natural Language Processing Basics

Part of Speech Tagging and Named Entity Recognition

Text Classification

Semantics and Sentiment Analysis

Topic Modeling

Deep Learning for NLP

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