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The Complete Guide to TensorFlow 1.x
Become an expert in machine learning and deep learning with the new TensorFlow 1.x
About This BookLearn to implement TensorFlow in productionPerform highly accurate and efficient numerical computing with TensorFlowUnlock the advanced techniques that bring more accuracy and speed to machine learning activitiesExplore various possibilities with deep learning and gain amazing insights from dataWho This Book Is ForAre you a data analyst, data scientist, or a researcher looking forward to a guide that will help you increase the speed and efficiency of your machine learning activities? If yes, then this course is for you!
What You Will LearnLearn about machine learning landscapes along with the historical development and progress of deep learningLoad, interact, process, and save complex datasetsSolve classification and regression problems using state-of-the-art techniquesTrain machines quickly to learn from data by exploring reinforcement learning techniquesClassify images using deep neural network schemesLearn about deep machine intelligence and GPU computingExplore active areas of deep learning research and applicationsIn DetailThe aim of the course is to help you tackle the common commercial machine learning and deep learning problems that you’re facing in your day-to-day activities.
This Learning Journey begins with an introduction to machine learning and deep learning. You will explore the main features and capabilities of TensorFlow such as computation graph, data model, programming model, and TensorBoard. The key highlight is the course will teach you how to upgrade our code from TensorFlow 0.x to TensorFlow 1.x. Next, you will learn the different techniques of machine learning such as clustering, linear regression, and logistic regression with the help of real-world projects and examples. You will also learn the concepts of reinforcement learning, the Q-learning algorithm, and the OpenAI Gym framework. Moving ahead you will dive into neural networks and see how convolution, recurrent, and deep neural networks work and the main operation types used in building them. Next, you will learn the advanced concepts such as GPU computing and multimedia programming. Finally, the course demonstrate an example on deep learning on Android using TensorFlow.
By the end of this course, you will have a solid knowledge of the all-new TensorFlow and be able to implement it efficiently in production.
Style and approachThis course takes a step-by-step approach to teach you how to implement TensorFlow in production. Starting with the basics of TensorFlow, you will learn machine learning and deep learning techniques, along with the advanced concepts of TensorFlow. With the help of real-world projects and examples, this course will help you apply Tensorflow's features from scratch.
This course is a blend of text, videos, code examples, and assessments, all packaged up keeping your journey in mind. The curator of this course has combined some of the best that Packt has to offer in one complete package. It includes content from the following Packt
Building Machine Learning Systems with TensorFlow by Rodolfo Bonnin Deep Learning with TensorFlow by Giancarlo Zaccone, Md. Rezaul Karim, and Ahmed Menshawy
About This BookLearn to implement TensorFlow in productionPerform highly accurate and efficient numerical computing with TensorFlowUnlock the advanced techniques that bring more accuracy and speed to machine learning activitiesExplore various possibilities with deep learning and gain amazing insights from dataWho This Book Is ForAre you a data analyst, data scientist, or a researcher looking forward to a guide that will help you increase the speed and efficiency of your machine learning activities? If yes, then this course is for you!
What You Will LearnLearn about machine learning landscapes along with the historical development and progress of deep learningLoad, interact, process, and save complex datasetsSolve classification and regression problems using state-of-the-art techniquesTrain machines quickly to learn from data by exploring reinforcement learning techniquesClassify images using deep neural network schemesLearn about deep machine intelligence and GPU computingExplore active areas of deep learning research and applicationsIn DetailThe aim of the course is to help you tackle the common commercial machine learning and deep learning problems that you’re facing in your day-to-day activities.
This Learning Journey begins with an introduction to machine learning and deep learning. You will explore the main features and capabilities of TensorFlow such as computation graph, data model, programming model, and TensorBoard. The key highlight is the course will teach you how to upgrade our code from TensorFlow 0.x to TensorFlow 1.x. Next, you will learn the different techniques of machine learning such as clustering, linear regression, and logistic regression with the help of real-world projects and examples. You will also learn the concepts of reinforcement learning, the Q-learning algorithm, and the OpenAI Gym framework. Moving ahead you will dive into neural networks and see how convolution, recurrent, and deep neural networks work and the main operation types used in building them. Next, you will learn the advanced concepts such as GPU computing and multimedia programming. Finally, the course demonstrate an example on deep learning on Android using TensorFlow.
By the end of this course, you will have a solid knowledge of the all-new TensorFlow and be able to implement it efficiently in production.
Style and approachThis course takes a step-by-step approach to teach you how to implement TensorFlow in production. Starting with the basics of TensorFlow, you will learn machine learning and deep learning techniques, along with the advanced concepts of TensorFlow. With the help of real-world projects and examples, this course will help you apply Tensorflow's features from scratch.
This course is a blend of text, videos, code examples, and assessments, all packaged up keeping your journey in mind. The curator of this course has combined some of the best that Packt has to offer in one complete package. It includes content from the following Packt
Building Machine Learning Systems with TensorFlow by Rodolfo Bonnin Deep Learning with TensorFlow by Giancarlo Zaccone, Md. Rezaul Karim, and Ahmed Menshawy
322 pages, Kindle Edition
Published May 31, 2017
1 person is currently reading
4 people want to read
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