A complete guide for building machine learning and deep learning solutions using TensorFlow
About This Video
- The course combines theory and real-world applications to offer the most practical course that can help you learn TensorFlow in a systematic manner.
- It will show you how you can get started on machine learning, deep learning, and building your own neural networks from scratch.
Get your hands on the latest and easiest TensorFlow course. Devices are getting smarter thanks to machine learning and artificial intelligence, and that is definitely going to continue. Machines are going to continue getting better and evolve, making tasks easier for humans. With machine learning and AI in the picture, the role of TensorFlow is unavoidable. TensorFlow is an open-source library that is commonly used for data flow programming. It also includes a symbolic math library that can be used for machine learning applications and neural networking. TensorFlow was built by the Google Brain Team for their internal development needs on AI and ML, before it was released to the public.However, it’s currently playing a huge role in helping technology advance to the next level. This makes TensorFlow a powerful technology to learn and master and this is exactly why we have designed this no-nonsense and no-fuss course. Unlike other courses that focus on just the basics, we’ve actually designed a full guide-based course to help you not only understand the fundamentals, but also learn the practical applications of TensorFlow. We’ve created this tutorial to show you the ins and outs of TensorFlow, including the foundation, life cycle, TensorBoard and so much more. The course starts with a detailed introduction into TensorFlow and its basics, including delving into the TensorFlow foundation. It also covers the machine learning life cycle, TensorBoard, logical regression, neural network basics, single and multiple hidden layer neural networks, convolutional neural networks, deep learning, and so much more! In the last section of the course, you’ll use everything you’ve learned throughout the course to build an actual project from scratch. So, what are you waiting for? Enroll now and get started with building your very own neural networks with TensorFlow.
Table of Contents
Chapter 1 : Introduction
- Introduction 00:00:35
- Chapter 2 : Tensorflow Foundations
- Chapter 3 : ML lifecycle & TensorBoard
- Chapter 4 : The Machine Learning Lifecycle & Using TensorBoard
- Chapter 5 : Logistic Regression & NN Basics
- Chapter 6 : Single & Multiple Hidden Layer NNs
- Chapter 7 : Convolutional NNs
- Chapter 8 : Deep Learning
- Chapter 9 : Final Project
- Title: TensorFlow for Beginners
- Release date: April 2018
- Publisher(s): Packt Publishing
- ISBN: 9781789344288