News classification using CNN, Keras and word embeddings

Course Description

Learn to build news classification engine with CNN, keras, Glove and  popular programming language Python.

Build a strong foundation in text classification with this tutorial for beginners.

• Understanding of text classification

• Understand the world of world embeddings

• Learn CNN from scratch

• Leverage CNN, Keras, Glove to classify news

• Learn how to represent text as numeric vectors using glove embeddings

• Learn how to evaluate model from scratch

• User Jupyter Notebook for programming

• Build a real life web application to classify news

  
  

• A Powerful Skill at Your Fingertips  Learning the fundamentals of text classification puts a powerful and very useful tool at your fingertips. Python and Jupyter are free, easy to learn, has excellent documentation.

No prior knowledge of deep learning or Machine learning is assumed. I a, covering topics like CNN, Word Embeddings Precision, Recall in depth so that  even beginners can understand this course very well.

Jobs in text classification systems area are plentiful, and being able to learn it with CNN and Keras will give you a strong edge.

Text Classification ares becoming very popular. Washington Post, News York Times, Amazon,  Google eCommerce websites are few famous example of text classification systems in action.  Text classification systems are vital in information retrieval and personalizing news.  Learning CNN with Keras will help you become a natural language processing (NLP) developer which is in high demand.

Content and Overview  

This course teaches you on how to build news classification system using open source Python and Jupyter framework.  You will work along with me step by step to build following answers

• Introduction to text classification systems.

• Introduction to CNN, Word Embeddings

• Build an jupyter notebook step by step using CNN and glove embeddings

• Build a real world web application to classify news

What am I going to get from this course?

• Learn text classification and build real news classification engine from professional trainer from your own desk.

• Over 10 lectures teaching you how to build news classification systems

• Suitable for beginner programmers and ideal for users who learn faster when shown.

• Visual training method, offering users increased retention and accelerated learning.

• Breaks even the most complex applications down into simplistic steps.

• Offers challenges to students to enable reinforcement of concepts. Also solutions are described to validate the challenges.

Note: Please note that I am using short documents in this example to illustrate concepts. You can use same code for longer documents as well.