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A Complete Natural Language Processing Masterclass™


A Complete Natural Language Processing Masterclass™

A Complete Natural Language Processing Masterclass™ Learn Core NLP Theory & Create Sentiment Analysis, Fake News Detector, Topic Modeling, LSTMs, Speech Recognition & More!

What you'll learn

  • Sentiment Analysis on Steam Video Game reviews.
  • Google Colab Cloud-Based Notebooks for using Python: to be up-to-date with what's being used in the Data Science world 2020!
  • Make your own product recommendation system.
  • Get comfortable using Python for NLP applications
  • Machine Learning for Language Applications
  • A good foundation in Linguistics to help learn NLP concepts.
  • Make Classifiers for Text Analysis.
  • Machine Learning Modelling Techniques
  • Create a Fake News Detector with Deep Learning
  • Deep Learning: Neural Networks, RNN, LSTM
  • Convert Speech To Text
  • Perform Speech Recognition

Requirements

  • No previous programming knowledge necessary. The lectures slowly explain the python syntax as you code alone with me.
  • New to Python: you get explanations of the code as you code along with me but not only that - theory slides explain concepts to help you understand what's going on behind the code.
  • No data science knowledge required: lectures teach how to work with data and key modelling concepts.
  • No NLP knowledge required. Linguistic concepts are taught to give a strong foundation of NLP even before you get into practical coding. This helps you to grasp NLP modelling techniques and cleaning concepts better.

Description

This course takes you from a beginner level to being able to understand NLP concepts, linguistic theory, and then practice these basic theories using Python - with very simple examples as you code along with me.

If you are new to Python or any computer programming, the course instructions make it easy for you to code together with me. I explain code line by line.

The gentle pace takes you gradually from these basics of NLP foundation to being able to understand Mathematical & Linguistic (English-Language based, Non-Mathematical) theories of Deep Learning.

Natural Language Processing Foundation

  • Linguistics & Semantics - study the background theory on natural language to better understand the Computer Science applications
  • Pre-processing Data (cleaning)
  • Regex, Tokenization, Stemming, Lemmatization
  • Part-of-Speech Tagging

The topics outlined below are taught using practical Python projects! 

  • Text Classification & Sentiment Analysis
  • Unsupervised Sentiment Analysis
  • Topic Modelling
  • Word Embedding with Deep Learning Models
  • LSTM using TensorFlow, Keras Sequence Model
  • Speech Recognition
  • Convert Speech to Text


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