English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 12m | 346 MB
Build NLP projects to enhance your portfolio
Natural Language Processing (NLP) is the field of Artificial Intelligence that deals with text analysis and understanding. Some of the fields in which NLP is widely used are sentiment classification, spam detection and topic detection. Deep Learning is one of the tools that helps us solving NLP problems.
This course will get you started with real world NLP projects and you will learn how to get the best from text data. We will be building and training models in real-world projects and focus on interactions between computers and humans with Tensorflow 2.0. Together we will dive deep in a collection of text, writing a jupyter notebook step by step until we obtain actionable insights and powerful visualizations.
By the end of the course, you will be able to build and implement your own NLP techniques and projects effectively with much ease confidently.
The course will have complete instruction to build a real world python pipeline based on tensorflow. Every step will be commented and explained with powerful visualizations that will be in the final code.
In the key parts of the pipeline useful tips will be provided so that you will end up being able to adapt and build your own Tensorflow pipeline. Everything will be focused on reproducing the real word problems.
What You Will Learn
- Create powerful NLP based Deep Learning Models with Tensorflow 2.0
- Learn to implement Word2Vec and seq2seq
- Design applications that deliver scores and state of the art Visualizations
- Build a text classification system (can be used for spam detection, sentiment analysis, and similar problems)
- Build a neural machine translation system
- Understand how to extract words to classify topics.
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