Building Machine Learning Projects with TensorFlow (eBook)

Engaging projects that will teach you how complex data can be exploited to gain the most insight

About This Book

• Bored of too much theory on TensorFlow? This book is what you need! Thirteen solid projects and four examples teach you how to implement TensorFlow in production.
• This example-rich guide teaches you how to perform highly accurate and efficient numerical computing with TensorFlow
• It is a practical and methodically explained guide that allows you to apply Tensorflow's features from the very beginning.

Who This Book Is For

This book is for data analysts, data scientists, and researchers who want to increase the speed and efficiency of their machine learning activities and results. Anyone looking for a fresh guide to complex numerical computations with TensorFlow will find this an extremely helpful resource. This book is also for developers who want to implement TensorFlow in production in various scenarios. Some experience with C++ and Python is expected.

What You Will Learn

• Load, interact, dissect, process, and save complex datasets
• Solve classification and regression problems using state of the art techniques
• Predict the outcome of a simple time series using Linear Regression modeling
• Use a Logistic Regression scheme to predict the future result of a time series
• Classify images using deep neural network schemes
• Tag a set of images and detect features using a deep neural network, including a Convolutional Neural Network (CNN) layer
• Resolve character recognition problems using the Recurrent Neural Network (RNN) model

In Detail

This book of projects highlights how TensorFlow can be used in different scenarios - this includes projects for training models, machine learning, deep learning, and working with various neural networks. Each project provides exciting and insightful exercises that will teach you how to use TensorFlow and show you how layers of data can be explored by working with Tensors. Simply pick a project that is in line with your environment and get stacks of information on how to implement TensorFlow in production.

Style and approach

This book is a practical guide to implementing TensorFlow in production. It explores various scenarios in which you could use TensorFlow and shows you how to use it in the context of real world projects. This will not only give you an upper hand in the field, but shows the potential for innovative uses of TensorFlow in your environment. This guide opens the door to second generation machine learning and numerical computation - a must-have for your bookshelf!

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Engaging projects that will teach you how complex data can be exploited to gain the most insightAbout This BookBored of too much theory on TensorFlow? This book is what you need! Thirteen solid projects and four examples teach you how to implement TensorFlow in production.This example-rich guide teaches you how to perform highly accurate and efficient numerical computing with TensorFlowIt is a practical and methodically explained guide that allows you to apply Tensorflow's features from the very beginning.Who This Book Is ForThis book is for data analysts, data scientists, and researchers who want to increase the speed and efficiency of their machine learning activities and results. Anyone looking for a fresh guide to complex numerical computations with TensorFlow will find this an extremely helpful resource. This book is also for developers who want to implement TensorFlow in production in various scenarios. Some experience with C++ and Python is expected.What You Will LearnLoad, interact, dissect, process, and save complex datasetsSolve classification and regression problems using state of the art techniques Predict the outcome of a simple time series using Linear Regression modelingUse a Logistic Regression scheme to predict the future result of a time seriesClassify images using deep neural network schemesTag a set of images and detect features using a deep neural network, including a Convolutional Neural Network (CNN) layerResolve character recognition problems using the Recurrent Neural Network (RNN) modelIn DetailThis book of projects highlights how TensorFlow can be used in different scenarios - this includes projects for training models, machine learning, deep learning, and working with various neural networks. Each project provides exciting and insightful exercises that will teach you how to use TensorFlow and show you how layers of data can be explored by working with Tensors. Simply pick a project that is in line with your environment and get stacks of information on how to implement TensorFlow in production.Style and approachThis book is a practical guide to implementing TensorFlow in production. It explores various scenarios in which you could use TensorFlow and shows you how to use it in the context of real world projects. This will not only give you an upper hand in the field, but shows the potential for innovative uses of TensorFlow in your environment. This guide opens the door to second generation machine learning and numerical computation - a must-have for your bookshelf!