Overview:

Robusta's Natural Language Processing course will give you a detailed look at the science of applying machine learning algorithms to process large amounts of n atural language data. You will learn the concepts of statistical machine translation and neural models, deep semantic similarity model (DSSM), neural knowledge base embedding, deep reinforcement learning technique, neural models applied in image captioning, and visual question answering using Python’s Natural Language Toolkit (NLTK)

Duration: 

40 hours

Intended Audience:

The course is ideal for anyone who wants to become familiar with this emerging and exciting domain of AI, including:

-          Data scientists

-          Analytics managers

-          Data analysts

-          Data engineers

-          Data architects

Prerequisites:

Learners who attend this course should have a basic understanding of:

-          Math and statistics

-          Data science 

-          Machine learning

Cousre Objectives:

After completing this NLP training in Python, you will be able to:

-          Apply deep learning models to solve machine translation and conversation problems

-          Implement deep structured semantic models (DSSM) to retrieve information

-          Understand deep reinforcement learning techniques applied in NLP

-          Use neural models applied in Image captioning and visual question answering

Course outlines:

1.      Working with Text Corpus

2.      Processing Raw Text with NLTK

3.      A Practical Real World Example of Text Classification

4.      Finding Useful Information from Piles of Text

5.      Developing a Speech to Text Application Using Python