MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 3 hours 50 minutes | English | 798 MBVideo DescriptionDeep 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 ApproachThis 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.

Table of ContentsEXPLORING ESSENTIAL DEEP LEARNING TERMS AND TOOLSPREDICTING DEMAND FOR AIRLINE TRAVELIDENTIFYING MEAN TWEETSDETECTING SMILES IN YOUR CAMERA APPPREDICTING STOCK PRICES USING LSTM