Hands-on Deep Learning with TensorFlow [Video]

Build smart systems with ease using TensorFlow; Video Course

Are you short on time to start from scratch to use deep learning to solve complex problems involving topics like neural networks and reinforcement learning? If yes, then this is the course to help you. This course is designed to help you to overcome various data science problems by using efficient deep learning models built in TensorFlow.The course begins with a quick introduction to TensorFlow essentials. Next, we start with deep neural networks for different problems and then explore the applications of Convolutional Neural Networks on two real datasets. If you’re facing time series problem then we will show you how to tackle it using RNN. We will also highlight how autoencoders can be used for efficient data representation. Lastly, we will take you through some of the important techniques to implement generative adversarial networks. All these modules are developed with step by step TensorFlow implementation with the help of real examples.By the end of the course you will be able to develop deep learning based solutions to any kind of problem you have, without any need to learn deep learning models from scratch, rather using tensorflow and it’s enormous power.

https://github.com/PacktPublishing/Hands-on-Deep-Learning-with-TensorFlow-v

Style and Approach

This is a hands-on course covering important deep learning techniques with TensorFlow and using practical examples. Throughout the course, you'll learn to work with different algorithms and follow step-by-step instructions to implement them using different example real-world

What You Will Learn

• Use the power of TensorFlow to help you in your daily deep learning tasks
• Build a base for TensorFlow by implementing regression
• Solve prediction deep learning problems with TensorFlow
• Solve Image classification deep learning problems with TensorFlow
• Tackle the potential of RNN and LSTM Neural Networks with TensorFlow to solve time series problems
• Utilize the power of efficient data representation using autoencoders
• Effective ways to implement generative adversarial networks in the real world
• Get equipped to develop projects with deep learning

Authors

Salil Vishnu Kapur

Salil Vishnu Kapur is a Data Science Researcher at the Institute for Big Data Analytics,Dalhousie University. He is extremely passionate about Machine Learning, Deep Learning, Data mining and Big Data Analytics. Salil has around 3 years of experience working with these technologies as a Senior Analyst in Capgemini, prior to that as an intern at IIT Bombay through the FOSSEE Python TextBook Companion Project and presently with the Department of Fisheries and Transport Canada through Dalhousie University.