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Hands On Artificial Intelligence With Tensorflow

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Hands On Artificial Intelligence With Tensorflow

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Author : Amir Ziai
language : en
Publisher:
Release Date : 2018-10-31

Hands On Artificial Intelligence With Tensorflow written by Amir Ziai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Artificial intelligence categories.

Book Description Artificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more. Hands-On Artificial Intelligence with TensorFlow gives you a rundown of essential AI concepts and their implementation with TensorFlow, also highlighting different approaches to solving AI problems using machine learning and deep learning techniques. In addition to this, the book covers advanced concepts, such as reinforcement learning, generative adversarial networks (GANs), and multimodal learning. Once you have grasped all this, you'll move on to exploring GPU computing and neuromorphic computing, along with the latest trends in quantum computing. You'll work through case studies that will help you examine AI applications in the important areas of computer vision, healthcare, and FinTech, and analyze their datasets. In the concluding chapters, you'll briefly investigate possible developments in AI that we can expect to see in the future. By the end of this book, you will be well-versed with the essential concepts of AI and their implementation using TensorFlow. What you will learn Explore the core concepts of AI and its different approaches Use the TensorFlow framework for smart applications Implement various machine and deep learning algorithms with TensorFlow Design self-learning RL systems and implement generative models Perform GPU computing efficiently using best practices Build enterprise-grade apps for computer vision, NLP, and healthcare Who this book is for Hands-On Artificial Intelligence with TensorFlow is for you if you are a machine learning developer, data scientist, AI researcher, or anyone who wants to build artificial intelligence applications using TensorFlow. You need to have some working knowledge of machine learning to get the most out of this book.

Hands On Machine Learning With Scikit Learn Keras And Tensorflow

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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-09-05

Hands On Machine Learning With Scikit Learn Keras And Tensorflow written by Aurélien Géron and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-05 with Computers categories.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets

Hands On Machine Learning With Scikit Learn And Tensorflow

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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-03-13

Hands On Machine Learning With Scikit Learn And Tensorflow written by Aurélien Géron and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-13 with Computers categories.

Hands On Machine Learning With Scikit Learn Keras And Tensorflow

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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-10-04

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning

Hands On Artificial Intelligence With Tensorflow

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Author : Saikat Basak
language : en
Publisher:
Release Date : 2018

Hands On Artificial Intelligence With Tensorflow written by Saikat Basak and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.

"TensorFlow is one of the most commonly used frameworks for Deep Learning and AI. This course will be your guide to understand and learn the concepts of Artificial intelligence by applying them in a real-world project with TensorFlow. This course will show you how to combine the power of Artificial Intelligence and TensorFlow to develop some exciting applications for the real world. This course will take you through all the relevant AI domains, tools, and algorithms required to build optimal solutions and will show you how to implement them hands-on. You will then be taken through techniques such as reinforcement learning, heuristic searches, neural networks, Computer Vision, OpenAI Gym, and more in different stages of your application. This course will show you how to implement AI practically using TensorFlow models and how it eases the way you interact with the technology. You will learn how TensorFlow can be used to analyze a variety of data sets and will learn to optimize various AI algorithms. By the end of the course, you will have learned to build intelligent apps by leveraging the full potential of Artificial Intelligence with TensorFlow."--Resource description page.

Hands On Computer Vision With Tensorflow 2

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Author : Benjamin Planche
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-30

Hands On Computer Vision With Tensorflow 2 written by Benjamin Planche and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Computers categories.

A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performanceBook Description Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learnCreate your own neural networks from scratchClassify images with modern architectures including Inception and ResNetDetect and segment objects in images with YOLO, Mask R-CNN, and U-NetTackle problems faced when developing self-driving cars and facial emotion recognition systemsBoost your application's performance with transfer learning, GANs, and domain adaptationUse recurrent neural networks (RNNs) for video analysisOptimize and deploy your networks on mobile devices and in the browserWho this book is for If you're new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you're an expert curious about the new TensorFlow 2 features, you'll find this book useful. While some theoretical concepts require knowledge of algebra and calculus, the book covers concrete examples focused on practical applications such as visual recognition for self-driving cars and smartphone apps.

Hands On Transfer Learning With Python

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Author : Dipanjan Sarkar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-08-31

Hands On Transfer Learning With Python written by Dipanjan Sarkar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-31 with Computers categories.

Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem Key Features Build deep learning models with transfer learning principles in Python implement transfer learning to solve real-world research problems Perform complex operations such as image captioning neural style transfer Book Description Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems. The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP). By the end of this book, you will be able to implement both DL and transfer learning principles in your own systems. What you will learn Set up your own DL environment with graphics processing unit (GPU) and Cloud support Delve into transfer learning principles with ML and DL models Explore various DL architectures, including CNN, LSTM, and capsule networks Learn about data and network representation and loss functions Get to grips with models and strategies in transfer learning Walk through potential challenges in building complex transfer learning models from scratch Explore real-world research problems related to computer vision and audio analysis Understand how transfer learning can be leveraged in NLP Who this book is for Hands-On Transfer Learning with Python is for data scientists, machine learning engineers, analysts and developers with an interest in data and applying state-of-the-art transfer learning methodologies to solve tough real-world problems. Basic proficiency in machine learning and Python is required.

Hands On Deep Learning Architectures With Python

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Author : Yuxi (Hayden) Liu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-04-30

Hands On Deep Learning Architectures With Python written by Yuxi (Hayden) Liu and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-30 with Computers categories.

Concepts, tools, and techniques to explore deep learning architectures and methodologies Key FeaturesExplore advanced deep learning architectures using various datasets and frameworksImplement deep architectures for neural network models such as CNN, RNN, GAN, and many moreDiscover design patterns and different challenges for various deep learning architecturesBook Description Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and implement deep learning architectures to resolve various deep learning research problems. Hands-On Deep Learning Architectures with Python explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations and ideas to help you build efficient artificial intelligence systems (AI), this book will help you learn how neural networks play a major role in building deep architectures. You will understand various deep learning architectures (such as AlexNet, VGG Net, GoogleNet) with easy-to-follow code and diagrams. In addition to this, the book will also guide you in building and training various deep architectures such as the Boltzmann mechanism, autoencoders, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), GAN, and more—all with practical implementations. By the end of this book, you will be able to construct deep models using popular frameworks and datasets with the required design patterns for each architecture. You will be ready to explore the potential of deep architectures in today's world. What you will learnImplement CNNs, RNNs, and other commonly used architectures with PythonExplore architectures such as VGGNet, AlexNet, and GoogLeNetBuild deep learning architectures for AI applications such as face and image recognition, fraud detection, and many moreUnderstand the architectures and applications of Boltzmann machines and autoencoders with concrete examples Master artificial intelligence and neural network concepts and apply them to your architectureUnderstand deep learning architectures for mobile and embedded systemsWho this book is for If you’re a data scientist, machine learning developer/engineer, or deep learning practitioner, or are curious about AI and want to upgrade your knowledge of various deep learning architectures, this book will appeal to you. You are expected to have some knowledge of statistics and machine learning algorithms to get the best out of this book

The Tensorflow Workshop

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Author : Matthew Moocarme
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-12-15

The Tensorflow Workshop written by Matthew Moocarme and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-15 with Computers categories.

Get started with TensorFlow fundamentals to build and train deep learning models with real-world data, practical exercises, and challenging activities Key FeaturesUnderstand the fundamentals of tensors, neural networks, and deep learningDiscover how to implement and fine-tune deep learning models for real-world datasetsBuild your experience and confidence with hands-on exercises and activitiesBook Description Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging. If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it'll quickly get you up and running. You'll start off with the basics – learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you'll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models. Building on this solid foundation, you'll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing. By the end of this deep learning book, you'll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow. What you will learnGet to grips with TensorFlow's mathematical operationsPre-process a wide variety of tabular, sequential, and image dataUnderstand the purpose and usage of different deep learning layersPerform hyperparameter-tuning to prevent overfitting of training dataUse pre-trained models to speed up the development of learning modelsGenerate new data based on existing patterns using generative modelsWho this book is for This TensorFlow book is for anyone who wants to develop their understanding of deep learning and get started building neural networks with TensorFlow. Basic knowledge of Python programming and its libraries, as well as a general understanding of the fundamentals of data science and machine learning, will help you grasp the topics covered in this book more easily.

Hands On Artificial Intelligence For Beginners

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Author : Patrick D. Smith
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-10-31

Hands On Artificial Intelligence For Beginners written by Patrick D. Smith and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.

Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease Key FeaturesEnter the world of AI with the help of solid concepts and real-world use casesExplore AI components to build real-world automated intelligenceBecome well versed with machine learning and deep learning conceptsBook Description Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world. Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games. By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications. What you will learnUse TensorFlow packages to create AI systemsBuild feedforward, convolutional, and recurrent neural networksImplement generative models for text generationBuild reinforcement learning algorithms to play gamesAssemble RNNs, CNNs, and decoders to create an intelligent assistantUtilize RNNs to predict stock market behaviorCreate and scale training pipelines and deployment architectures for AI systemsWho this book is for This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.

Hands On Artificial Intelligence With Tensorflow

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