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Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks

AI Self-Driving Cars Accordance - Practical Advances In Artificial Intelligence And Machine Learning (Paperback): Lance Eliot AI Self-Driving Cars Accordance - Practical Advances In Artificial Intelligence And Machine Learning (Paperback)
Lance Eliot
R715 Discovery Miles 7 150 Ships in 10 - 15 working days
AI Self-Driving Cars Consonance - Practical Advances in Artificial Intelligence and Machine Learning (Paperback): Lance Eliot AI Self-Driving Cars Consonance - Practical Advances in Artificial Intelligence and Machine Learning (Paperback)
Lance Eliot
R737 Discovery Miles 7 370 Ships in 10 - 15 working days
Neural Networks for Pattern Recognition (Paperback): Christopher M. Bishop Neural Networks for Pattern Recognition (Paperback)
Christopher M. Bishop; Foreword by Geoffrey Hinton
R2,684 Discovery Miles 26 840 Ships in 12 - 19 working days

This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. The author introduces the basic principles of pattern recognition and then goes on to describe techniques for modelling probability density functions, and discusses the properties and relative merits of the multi-layer perceptron and radial basis function network models. This book is designed with graduate students in mind and throughout the text it motivates the use of various forms of error functions and reviews the principal algorithms for error function minimization. Bishop also covers the fundamental topics of data processing, feature extraction, and prior knowledge and concludes with an extensive treatment of Bayesian techniques and their applications to neural networks.

Immersion Into Noise (second edition) (Paperback): Joseph Nechvatal Immersion Into Noise (second edition) (Paperback)
Joseph Nechvatal
R596 Discovery Miles 5 960 Ships in 10 - 15 working days
Applied Neural Networks for Signal Processing (Paperback, New ed): Fa-Long Luo, Rolf Unbehauen Applied Neural Networks for Signal Processing (Paperback, New ed)
Fa-Long Luo, Rolf Unbehauen
R1,969 Discovery Miles 19 690 Ships in 12 - 19 working days

The use of neural networks in signal processing is becoming increasingly widespread, with applications in many areas. Applied Neural Networks for Signal Processing is the first book to provide a comprehensive introduction to this broad field. It begins by covering the basic principles and models of neural networks in signal processing. The authors then discuss a number of powerful algorithms and architectures for a range of important problems, and describe practical implementation procedures. A key feature of the book is that many carefully designed simulation examples are included to help guide the reader in the development of systems for new applications. The book will be an invaluable reference for scientists and engineers working in communications, control or any other field related to signal processing. It can also be used as a textbook for graduate courses in electrical engineering and computer science.

AI Self-Driving Cars Vicissitude - Practical Advances in Artificial Intelligence and Machine Learning (Paperback): Lance Eliot AI Self-Driving Cars Vicissitude - Practical Advances in Artificial Intelligence and Machine Learning (Paperback)
Lance Eliot
R732 Discovery Miles 7 320 Ships in 10 - 15 working days
GANs Interview Questions - with detailed answers (Paperback): Saroj Mali, Geoffrey Ziskovin, Aditya Chatterjee GANs Interview Questions - with detailed answers (Paperback)
Saroj Mali, Geoffrey Ziskovin, Aditya Chatterjee
R317 Discovery Miles 3 170 Ships in 10 - 15 working days
Machine Learning - Getting Started - Launch yourself into machine learning! (Paperback): Ananda Soundhararajan Machine Learning - Getting Started - Launch yourself into machine learning! (Paperback)
Ananda Soundhararajan
R359 Discovery Miles 3 590 Ships in 10 - 15 working days
Mastering PyTorch - - Build powerful deep learning architectures using advanced PyTorch features (Paperback, 2nd Revised... Mastering PyTorch - - Build powerful deep learning architectures using advanced PyTorch features (Paperback, 2nd Revised edition)
Ashish Ranjan Jha
R1,256 Discovery Miles 12 560 Ships in 10 - 15 working days

Master advanced techniques and algorithms for machine learning with PyTorch using real-world examples Key Features * Understand how to use PyTorch to build advanced neural network models including graph neural networks and reinforcement learning models * Learn the latest tech, such as generating images from text using diffusion models * Become an expert in deploying PyTorch models in the cloud, on mobile and across platforms * Get the best from PyTorch by working with key libraries, including Hugging Face, fast.ai, and PyTorch Lightning Book Description PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch book will help you uncover expert techniques to get the most from your data and build complex neural network models. You'll create convolutional neural networks (CNNs) for image classification and recurrent neural networks (RNNs) and transformers for sentiment analysis. As you advance, you'll apply deep learning across different domains, such as music, text, and image generation using generative models. You'll not only build and train your own deep reinforcement learning models in PyTorch but also deploy PyTorch models to production, including mobiles and embedded devices. Finally, you'll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep learning toolbelt, teaching you how to use fast.ai for prototyping models to training models using PyTorch Lightning. You'll discover libraries for AutoML and explainable AI, create recommendation systems using TorchRec, and build language and vision transformers with Hugging Face. By the end of this PyTorch book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models. What you will learn * Implement text, image, and music generating models using PyTorch * Build a deep Q-network (DQN) model in PyTorch * Deploy PyTorch models on mobiles and embedded devices * Become well-versed with rapid prototyping using PyTorch with fast.ai * Perform neural architecture search effectively using AutoML * Easily interpret machine learning models using Captum * Develop your own recommendation system using TorchRec * Design ResNets, LSTMs, and graph neural networks * Create language and vision transformer models using Hugging Face Who This Book Is For This book is for data scientists, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning models using PyTorch. This book is an ideal resource for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep learning with Python programming is required.

Hybrid Data Science (HDS) Modeling Approaches for Industrial and Scientific Applications (Paperback): Keshava Prasad... Hybrid Data Science (HDS) Modeling Approaches for Industrial and Scientific Applications (Paperback)
Keshava Prasad Rangarajan, Egidio Marotta, Srinath Madasu
R4,475 Discovery Miles 44 750 Ships in 10 - 15 working days
Python - This Book Includes: The Guide for Beginners, Machine Learning (Paperback): Josh Hugh Learning Python - This Book Includes: The Guide for Beginners, Machine Learning (Paperback)
Josh Hugh Learning
R492 Discovery Miles 4 920 Ships in 10 - 15 working days
3D Deep Learning with Python - Design and develop your computer vision model with 3D data using PyTorch3D and more (Paperback):... 3D Deep Learning with Python - Design and develop your computer vision model with 3D data using PyTorch3D and more (Paperback)
Xudong Ma, Vishakh Hegde, Lilit Yolyan
R1,037 Discovery Miles 10 370 Ships in 10 - 15 working days

Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with ease Key Features Understand 3D data processing with rendering, PyTorch optimization, and heterogeneous batching Implement differentiable rendering concepts with practical examples Discover how you can ease your work with the latest 3D deep learning techniques using PyTorch3D Book DescriptionWith this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. What you will learn Develop 3D computer vision models for interacting with the environment Get to grips with 3D data handling with point clouds, meshes, ply, and obj file format Work with 3D geometry, camera models, and coordination and convert between them Understand concepts of rendering, shading, and more with ease Implement differential rendering for many 3D deep learning models Advanced state-of-the-art 3D deep learning models like Nerf, synsin, mesh RCNN Who this book is forThis book is for beginner to intermediate-level machine learning practitioners, data scientists, ML engineers, and DL engineers who are looking to become well-versed with computer vision techniques using 3D data.

Network Programming in Python - The Basic: A Detailed Guide to Python 3 Network Programming and Management (English Edition)... Network Programming in Python - The Basic: A Detailed Guide to Python 3 Network Programming and Management (English Edition) (Paperback)
John Galbraith
R903 Discovery Miles 9 030 Ships in 10 - 15 working days
Machine Learning For Beginners (Paperback): Jonathan S Walker Machine Learning For Beginners (Paperback)
Jonathan S Walker
R378 R349 Discovery Miles 3 490 Save R29 (8%) Ships in 10 - 15 working days
Pytorch Deep Learning by Example, Vol. 2 - Applications - Grasp deep Learning from scratch like AlphaGo Zero within 40 days... Pytorch Deep Learning by Example, Vol. 2 - Applications - Grasp deep Learning from scratch like AlphaGo Zero within 40 days (3rd Edition) (Paperback)
Benjamin Young
R694 Discovery Miles 6 940 Ships in 10 - 15 working days
Predictive Analytics - The Secret to Predicting Future Events Using Big Data and Data Science Techniques Such as Data Mining,... Predictive Analytics - The Secret to Predicting Future Events Using Big Data and Data Science Techniques Such as Data Mining, Predictive Modelling, Statistics, Data Analysis, and Machine Learning (Paperback)
Richard Hurley
R367 Discovery Miles 3 670 Ships in 10 - 15 working days
AI Self-Driving Cars Headway - Practical Advances In Artificial Intelligence And Machine Learning (Paperback): Lance Eliot AI Self-Driving Cars Headway - Practical Advances In Artificial Intelligence And Machine Learning (Paperback)
Lance Eliot
R729 Discovery Miles 7 290 Ships in 10 - 15 working days
Ingenious Strides for AI Driverless Cars - Practical Advances in Artificial Intelligence and Machine Learning (Paperback):... Ingenious Strides for AI Driverless Cars - Practical Advances in Artificial Intelligence and Machine Learning (Paperback)
Lance Eliot
R724 Discovery Miles 7 240 Ships in 10 - 15 working days
AI Self-Driving Cars Trendsetting - Practical Advances In Artificial Intelligence And Machine Learning (Paperback): Lance Eliot AI Self-Driving Cars Trendsetting - Practical Advances In Artificial Intelligence And Machine Learning (Paperback)
Lance Eliot
R727 Discovery Miles 7 270 Ships in 10 - 15 working days
Beginning with Deep Learning Using TensorFlow - A Beginners Guide to TensorFlow and Keras for Practicing Deep Learning... Beginning with Deep Learning Using TensorFlow - A Beginners Guide to TensorFlow and Keras for Practicing Deep Learning Principles and Applications (Paperback)
Mohan Kumar Silaparasetty
R1,077 Discovery Miles 10 770 Ships in 10 - 15 working days
Practical Machine Learning with Spark - Uncover Apache Spark's Scalable Performance with High-Quality Algorithms Across... Practical Machine Learning with Spark - Uncover Apache Spark's Scalable Performance with High-Quality Algorithms Across NLP, Computer Vision and ML (English Edition) (Paperback)
Gourav Gupta, Manish Gupta, Inder Singh Gupta
R1,121 Discovery Miles 11 210 Ships in 10 - 15 working days
AI Self-Driving Cars Momentum - Practical Advances In Artificial Intelligence (Paperback): Lance Eliot AI Self-Driving Cars Momentum - Practical Advances In Artificial Intelligence (Paperback)
Lance Eliot
R731 Discovery Miles 7 310 Ships in 10 - 15 working days
Pytorch Deep Learning by Example Vol. 1 - Fundamentals - Grasp deep Learning from scratch like AlphaGo Zero within 40 days (3rd... Pytorch Deep Learning by Example Vol. 1 - Fundamentals - Grasp deep Learning from scratch like AlphaGo Zero within 40 days (3rd Edition) (Paperback)
Benjamin Young
R713 Discovery Miles 7 130 Ships in 10 - 15 working days
TensorFlow 2 Reinforcement Learning Cookbook - Over 50 recipes to help you build, train, and deploy learning agents for... TensorFlow 2 Reinforcement Learning Cookbook - Over 50 recipes to help you build, train, and deploy learning agents for real-world applications (Paperback)
Praveen Palanisamy
R1,190 Discovery Miles 11 900 Ships in 10 - 15 working days

Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key Features Develop and deploy deep reinforcement learning-based solutions to production pipelines, products, and services Explore popular reinforcement learning algorithms such as Q-learning, SARSA, and the actor-critic method Customize and build RL-based applications for performing real-world tasks Book DescriptionWith deep reinforcement learning, you can build intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework used to develop and train deep neural networks (DNNs). This book contains easy-to-follow recipes for leveraging TensorFlow 2.x to develop artificial intelligence applications. Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers OpenAI Gym, model-based RL, model-free RL, and how to develop basic agents. You'll discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. As you advance, you'll explore the applications of reinforcement learning by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Finally, you'll find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x. By the end of this TensorFlow book, you'll have gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch. What you will learn Build deep reinforcement learning agents from scratch using the all-new TensorFlow 2.x and Keras API Implement state-of-the-art deep reinforcement learning algorithms using minimal code Build, train, and package deep RL agents for cryptocurrency and stock trading Deploy RL agents to the cloud and edge to test them by creating desktop, web, and mobile apps and cloud services Speed up agent development using distributed DNN model training Explore distributed deep RL architectures and discover opportunities in AIaaS (AI as a Service) Who this book is forThe book is for machine learning application developers, AI and applied AI researchers, data scientists, deep learning practitioners, and students with a basic understanding of reinforcement learning concepts who want to build, train, and deploy their own reinforcement learning systems from scratch using TensorFlow 2.x.

Deep Learning With Python - A Comprehensive Guide Beyond The Basics (Paperback): Travis Booth Deep Learning With Python - A Comprehensive Guide Beyond The Basics (Paperback)
Travis Booth
R544 Discovery Miles 5 440 Ships in 10 - 15 working days
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