Posted on 2019-01-25, by everest555.
Real-World Python Deep Learning Projects
.MP4, AVC, 200 kbps, 1920x1080 | English, AAC, 160 kbps, 2 Ch | 3h 50m | 798 MB
Instructor: Jakub Konczyk
Identify mean tweets, detect smiles in your camera app, forecast stock prices, and more using Neural Networks
Deep Learning allows you to solve problems where traditional Machine Learning methods might perform poorly: detecting and extracting objects from images, extracting meaning from text, and predicting outcomes based on complex dependencies, to name a few. In this course you will learn how to use Deep Learning in practice by going through real-world examples.
You will start of by creating neural networks to predict the demand for airline travel in the future. Then, you'll run through a scenario where you have to identify negative tweets for a celebrity by using Convolutional Neural Networks (CNN's). Next you will create a neural network which will be able to identify smiles in your camera app. Finally, the last project will help you forecast a company's stock prices for the next day using Deep Learning.
By the end of this course, you will have a solid understanding of Deep Learning and the ability to build your own Deep Learning models.
Style and Approach
This course will teach you Deep Learning using easy-to-understand, practical, and clear examples. Each Deep Learning use case is based on a real-world dataset.
What You Will Learn
Build a solid understanding of common problems can you solve with Deep Learning
Use different Deep Learning algorithms to solve specific types of problem and learn their strengths and weaknesses,
Develop a clear understanding of how Deep Learning tools work and what you need to know to use them in practice
Discover the practical pros and cons of using Deep Learning
Save time by learning practical Deep Learning methods that you can immediately apply to real-world problems.
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