Transcend your machine learning experience by leveraging it with the cutting edge library - TensorFlow
About This Video
- This course is an easy-to-understand guide to the complexities of Google's TensorFlow framework; you'll build seven amazing projects throughout the course.
- This course is designed to balance theory and practical implementation, with complete Jupyter Notebook code guides and easy-reference practical examples.
- You'll also learn about the most cutting-edge machine-learning technology, deep learning, and we walk you through building an artificial neural network and a convolutional neural network step-by-step from scratch.
With this course you'll learn to take your data analysis and Python programming skills to the next level via Machine Learning using TensorFlow. This course focuses on key Machine Learning techniques and algorithms and you'll apply them practically using TensorFlow models in a hands-on approach. Each section covers a specific Machine Learning task and you will implement it on your system with TensorFlow models. For example, you will learn Logistic Regression and will then implement it with TensorFlow for your analysis tasks. You'll implement techniques such as Classification and Clustering effectively using TensorFlow. Similarly, this course takes you through different ML tasks/algorithms and teaches you to implement them in your applications/systems.
This course uses cuDNN 7.0, CUDA 9.0, and Python 3.5, while not the latest version available, it provides relevant and informative content for legacy users who wants to learn Machine Learning using TensorFlow.
Table of Contents
- Chapter 1 : Getting Started with TensorFlow
- Chapter 2 : Apply Regression Techniques in TensorFlow
Chapter 3 : Implementing Classification Techniques Using TensorFlow
- Performing Classification Techniques on Pima Indians Diabetes Dataset – Part 1 00:08:39
- Performing Classification Techniques on Pima Indians Diabetes Dataset – Part 2 00:04:20
- Performing Classification Techniques on Pima Indians Diabetes Dataset – Part 3 00:05:19
- Predicting Class of Income on Census Data – Part 1 00:04:22
- Predicting Class of Income on Census Data – Part 2 00:03:30
- Predicting Class of Income on Census Data – Part 3 00:05:04
- Chapter 4 : Implement Clustering Techniques in TensorFlow
- Chapter 5 : Create Your Own Artificial Neural Network
- Chapter 6 : Build Convolutional Neural Network Using Image Dataset
- Title: Hands-on Machine Learning with TensorFlow
- Release date: May 2018
- Publisher(s): Packt Publishing
- ISBN: 9781789136999