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Natural Language Processing with Deep Learning Course
Build Deep Learning Models for Natural Language Processing in Python using this complete guide
Lectures -60
Resources -9
Duration -2.5 hours
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Course Description
Natural Language Processing With Deep Learning Master Class course takes you closer to mastering Machine Learning and its applications. The machine learning engineer is the single most in-demand job on earth, according to the top job board.
This course is a practical manual. It serves as both a playbook and a workbook, encouraging you to gain knowledge through application to your own natural language projects. I advise working through every example in each session to get the most out of the course. You won't learn anything from this course if you treat it like a movie.
Natural Language Processing With Deep Learning Master Class Overview
Natural Language Processing is the field of study devoted to the automatic software manipulation of speech and text. You are constantly exposed to text through reading books, articles, blogs, tweets, the news, and increasingly, spoken words. Natural Language Processing is a long-established field of study that was first dominated by rule-based techniques created by linguists, then statistical techniques, and, more recently, deep learning techniques that hold a lot of promise.
Who is this course for?
Developers who have some background in applied machine learning and deep learning should take this course. Perhaps you need to start using deep learning for text in a project at work or for a research project. With the condensing of years' worth of knowledge and experience into a narrowly focused course of hands-on lessons, this course was created to assist you in doing that fast and effectively.
What are you going to Learn?
- Natural language processing definition.
- Defining deep learning and describing how it differs from existing machine learning techniques.
- What to do to get text data ready for modeling.
- How to use word embedding models to create distributed representations of text.
- How to create a model using a bag of words.
- How to create a neural sentiment analysis model that can predict a text document's class automatically.
- How to create a neural language model, which is necessary for any neural network that produces text.
- How to create a system for automatically creating textual descriptions for photos.
- How to create a neural machine translation program that can translate text between languages.
In the applied space machine learning is programming and programming is a hands-on sport.
“Mike's courses are popular with many of our clients." - Josh Gordon, Developer Advocate, Google
Goals
What will you learn in this course:
- You'll have a complete understanding of NLP specific to Deep Learning
- You'll learn how to properly prepare text for NLP models
- How to develop a Bag-of-Words model
- How to develop a neural language model
- You'll develop a photo captioning system and generate textual descriptions
- Create a neural machine translation system for translating text from one language to another
Prerequisites
What are the prerequisites for this course?
- Solid foundation in programming in Python
- Basic NumPy for array manipulation
- Solid understanding of machine learning principles
- Understand the basics of deep learning
- Basics of convolution neural networks
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
3 Lectures
- Introduction 01:39 01:39
- Course Overview 01:38 01:38
- Is this Course Right for You? 01:47 01:47
Foundations
6 Lectures
Data Preparation
6 Lectures
Bag-of-Words
8 Lectures
Word Embedding
6 Lectures
Text Classification
6 Lectures
Language Modeling
9 Lectures
Image Captioning
10 Lectures
Neural Machine Translation
5 Lectures
Instructor Details
Mike West
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