TensorFlow Deep Learning Projects : 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
Language: English
Published by Packt Publishing, 2018
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nach der Bestellung gedruckt Neuware - Printed after ordering - Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenariosKey FeaturesBuild efficient deep learning pipelines using the popular Tensorflow frameworkTrain neural networks such as ConvNets, generative models, and LSTMsIncludes projects related to Computer Vision, stock prediction, chatbots and moreBook DescriptionTensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games.By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently. What you will learnSet up the TensorFlow environment for deep learningConstruct your own ConvNets for effective image processingUse LSTMs for image caption generationForecast stock prediction accurately with an LSTM architectureLearn what semantic matching is by detecting duplicate Quora questionsSet up an AWS instance with TensorFlow to train GANsTrain and set up a chatbot to understand and interpret human inputBuild an AI capable of playing a video game by itself -and win it!Who this book is for:¿This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.…
Seller Inventory # 9781788398060
- Title
- TensorFlow Deep Learning Projects : 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
- Author
- Alberto Boschetti
- Publisher
- Packt Publishing
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1788398068
- ISBN 13
- 9781788398060
- Item weight
- 600 grams
- Dimensions
- 235x191x18 mm
Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios
Key Features
- Build efficient deep learning pipelines using the popular Tensorflow framework
- Train neural networks such as ConvNets, generative models, and LSTMs
- Includes projects related to Computer Vision, stock prediction, chatbots and more
Book Description
TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.
TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games.
By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.
What you will learn
- Set up the TensorFlow environment for deep learning
- Construct your own ConvNets for effective image processing
- Use LSTMs for image caption generation
- Forecast stock prediction accurately with an LSTM architecture
- Learn what semantic matching is by detecting duplicate Quora questions
- Set up an AWS instance with TensorFlow to train GANs
- Train and set up a chatbot to understand and interpret human input
- Build an AI capable of playing a video game by itself -and win it!
Who this book is for:
This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.
"Synopsis" may belong to another edition of this title.
About the Author
Having joined Kaggle over 10 years ago, Luca Massaron is a Kaggle Grandmaster in discussions and a Kaggle Master in competitions and notebooks. In Kaggle competitions he reached no. 7 in the worldwide rankings. On the professional side, Luca is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is a Google Developer Expert(GDE) in machine learning and the author of best-selling books on AI, machine learning, and algorithms.
Abhishek Thakur is a data scientist. His focus is mainly on applied machine learning and deep learning, rather than theoretical aspects. He completed his master's in computer science at the University of Bonn in early 2014. Since then, he has worked in various industries, with a research focus on automatic machine learning. He likes taking part in machine learning competitions and has attained a third place in the worldwide rankings on the popular website Kaggle.
"About the title" may belong to another edition of this title.
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last update: 01/06/2022
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