Ivan Gridin's Books

Learning Genetic Algorithms with Python

Empower the performance of Machine Learning and AI models with the capabilities of a powerful search algorithm (English Edition)

By: Ivan Gridin

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Learning Genetic Algorithms with Python

Empower the performance of Machine Learning and AI models with the capabilities of a powerful search algorithm (English Edition)

By: Ivan Gridin

Refuel your AI Models and ML applications with High-Quality Optimization and Search Solutions DESCRIPTION Genetic algorithms are one of the most straightforward and powerful techniques used in machine learning. This book ÔLearning Genetic Algorithms with PythonÕ guides the reader right from the basics of genetic algorithms to its real practical implementation in production environments.Ê Each of the chapters gives the reader an intuitive understanding of each concept. You will learn how to build a genetic algorithm from scratch and implement it in real-life problems. Covered with practical illustrated examples, you will learn to design and choose the best model architecture for the particular tasks. Cutting edge examples like radar and football manager problem statements, you will learn to solve high-dimensional big data challenges with ways of optimizing genetic algorithms. KEY FEATURESÊÊ _ Complete coverage on practical implementation of genetic algorithms. _ Intuitive explanations and visualizations supply theoretical concepts. _ Added examples and use-cases on the performance of genetic algorithms. _ Use of Python libraries and a niche coverage on the performance optimization of genetic algorithms. WHAT YOU WILL LEARNÊ _ Understand the mechanism of genetic algorithms using popular python libraries. _ Learn the principles and architecture of genetic algorithms. _ Apply and Solve planning, scheduling and analytics problems in Enterprise applications. _Ê Expert learning on prime concepts like Selection, Mutation and Crossover. WHO THIS BOOK IS FORÊÊ The book is for Data Science team, Analytics team, AI Engineers, ML Professionals who want to integrate genetic algorithms to refuel their ML and AI applications. No special expertise about machine learning is required although a basic knowledge of Python is expected. TABLE OF CONTENTS 1. Introduction 2. Genetic Algorithm Flow 3. Selection 4. Crossover 5. Mutation 6. Effectiveness 7. Parameter Tuning 8. Black-box Function 9. Combinatorial Optimization: Binary Gene Encoding 10. Combinatorial Optimization: Ordered Gene Encoding 11. Other Common Problems 12. Adaptive Genetic Algorithm 13. Improving Performance

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330

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BPB Publications

Published Date

ISBN 10

8194837758

ISBN 13

9788194837756

Time Series Forecasting using Deep Learning

Combining PyTorch, RNN, TCN, and Deep Neural Network Models to Provide Production-Ready Prediction Solutions (English Edition)

By: Ivan Gridin

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Time Series Forecasting using Deep Learning

Combining PyTorch, RNN, TCN, and Deep Neural Network Models to Provide Production-Ready Prediction Solutions (English Edition)

By: Ivan Gridin

Explore the infinite possibilities offered by Artificial Intelligence and Neural Networks KEY FEATURES ● Covers numerous concepts, techniques, best practices and troubleshooting tips by community experts. ● Includes practical demonstration of robust deep learning prediction models with exciting use-cases. ● Covers the use of the most powerful research toolkit such as Python, PyTorch, and Neural Network Intelligence. DESCRIPTION This book is amid at teaching the readers how to apply the deep learning techniques to the time series forecasting challenges and how to build prediction models using PyTorch. The readers will learn the fundamentals of PyTorch in the early stages of the book. Next, the time series forecasting is covered in greater depth after the programme has been developed. You will try to use machine learning to identify the patterns that can help us forecast the future results. It covers methodologies such as Recurrent Neural Network, Encoder-decoder model, and Temporal Convolutional Network, all of which are state-of-the-art neural network architectures. Furthermore, for good measure, we have also introduced the neural architecture search, which automates searching for an ideal neural network design for a certain task. Finally by the end of the book, readers would be able to solve complex real-world prediction issues by applying the models and strategies learnt throughout the course of the book. This book also offers another great way of mastering deep learning and its various techniques. WHAT YOU WILL LEARN ● Work with the Encoder-Decoder concept and Temporal Convolutional Network mechanics. ● Learn the basics of neural architecture search with Neural Network Intelligence. ● Combine standard statistical analysis methods with deep learning approaches. ● Automate the search for optimal predictive architecture. ● Design your custom neural network architecture for specific tasks. ● Apply predictive models to real-world problems of forecasting stock quotes, weather, and natural processes. WHO THIS BOOK IS FOR This book is written for engineers, data scientists, and stock traders who want to build time series forecasting programs using deep learning. Possessing some familiarity of Python is sufficient, while a basic understanding of machine learning is desirable but not needed. TABLE OF CONTENTS 1. Time Series Problems and Challenges 2. Deep Learning with PyTorch 3. Time Series as Deep Learning Problem 4. Recurrent Neural Networks 5. Advanced Forecasting Models 6. PyTorch Model Tuning with Neural Network Intelligence 7. Applying Deep Learning to Real-world Forecasting Problems 8. PyTorch Forecasting Package 9. What is Next?

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354

Publisher

BPB Publications

Published Date

ISBN 10

9391392571

ISBN 13

9789391392574

Practical Deep Reinforcement Learning with Python

Concise Implementation of Algorithms, Simplified Maths, and Effective Use of TensorFlow and PyTorch (English Edition)

By: Ivan Gridin

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Practical Deep Reinforcement Learning with Python

Concise Implementation of Algorithms, Simplified Maths, and Effective Use of TensorFlow and PyTorch (English Edition)

By: Ivan Gridin

Introducing Practical Smart Agents Development using Python, PyTorch, and TensorFlow KEY FEATURES ● Exposure to well-known RL techniques, including Monte-Carlo, Deep Q-Learning, Policy Gradient, and Actor-Critical. ● Hands-on experience with TensorFlow and PyTorch on Reinforcement Learning projects. ● Everything is concise, up-to-date, and visually explained with simplified mathematics. DESCRIPTION Reinforcement learning is a fascinating branch of AI that differs from standard machine learning in several ways. Adaptation and learning in an unpredictable environment is the part of this project. There are numerous real-world applications for reinforcement learning these days, including medical, gambling, human imitation activity, and robotics. This book introduces readers to reinforcement learning from a pragmatic point of view. The book does involve mathematics, but it does not attempt to overburden the reader, who is a beginner in the field of reinforcement learning. The book brings a lot of innovative methods to the reader's attention in much practical learning, including Monte-Carlo, Deep Q-Learning, Policy Gradient, and Actor-Critical methods. While you understand these techniques in detail, the book also provides a real implementation of these methods and techniques using the power of TensorFlow and PyTorch. The book covers some enticing projects that show the power of reinforcement learning, and not to mention that everything is concise, up-to-date, and visually explained. After finishing this book, the reader will have a thorough, intuitive understanding of modern reinforcement learning and its applications, which will tremendously aid them in delving into the interesting field of reinforcement learning. WHAT YOU WILL LEARN ● Familiarize yourself with the fundamentals of Reinforcement Learning and Deep Reinforcement Learning. ● Make use of Python and Gym framework to model an external environment. ● Apply classical Q-learning, Monte Carlo, Policy Gradient, and Thompson sampling techniques. ● Explore TensorFlow and PyTorch to practice the fundamentals of deep reinforcement learning. ● Design a smart agent for a particular problem using a specific technique. WHO THIS BOOK IS FOR This book is for machine learning engineers, deep learning fanatics, AI software developers, data scientists, and other data professionals eager to learn and apply Reinforcement Learning to ongoing projects. No specialized knowledge of machine learning is necessary; however, proficiency in Python is desired. TABLE OF CONTENTS Part I 1. Introducing Reinforcement Learning 2. Playing Monopoly and Markov Decision Process 3. Training in Gym 4. Struggling With Multi-Armed Bandits 5. Blackjack in Monte Carlo 6. Escaping Maze With Q-Learning 7. Discretization Part II. Deep Reinforcement Learning 8. TensorFlow, PyTorch, and Your First Neural Network 9. Deep Q-Network and Lunar Lander 10. Defending Atlantis With Double Deep Q-Network 11. From Q-Learning to Policy-Gradient 12. Stock Trading With Actor-Critic 13. What Is Next?

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Page Count

454

Publisher

BPB Publications

Published Date

ISBN 10

9355512058

ISBN 13

9789355512055

Practical Deep Reinforcement Learning with Python

Concise Implementation of Algorithms, Simplified Maths, and Effective Use of TensorFlow and PyTorch (English Edition)

By: Ivan Gridin

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Practical Deep Reinforcement Learning with Python

Concise Implementation of Algorithms, Simplified Maths, and Effective Use of TensorFlow and PyTorch (English Edition)

By: Ivan Gridin

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454

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BPB Publications

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ISBN 10

9355512058

ISBN 13

9789355512055

The Day Will Pass Away

The Diary of a Gulag Prison Guard: 1935-1936

By: Ivan Chistyakov

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The Day Will Pass Away

The Diary of a Gulag Prison Guard: 1935-1936

By: Ivan Chistyakov

A rare first-person testimony of the hardships of a Soviet labor camp—long suppressed—that will become a cornerstone of understanding the Soviet Union. Originally written in a couple of humble exercise books, which were anonymously donated to the Memorial Human Rights Centre in Moscow, this remarkable diary is one of the few first-person accounts to survive the sprawling Soviet prison system. At the back of these exercise books there is a blurred snapshot and a note, "Chistyakov, Ivan Petrovich, repressed in 1937-38. Killed at the front in Tula Province in 1941." This is all that remains of Ivan Chistyakov, a senior guard at the Baikal Amur Corrective Labour Camp. Who was this lost man? How did he end up in the gulag? Though a guard, he is a type of prisoner, too. We learn that he is a cultured and urbane ex-city dweller with a secret nostalgia for pre-Revolutionary Russia. In this diary, Chistyakov does not just record his life in the camp, he narrates it. He is a sharp-eyed witness and a sympathetic, humane, and broken man. From stumblingly poetic musings on the bitter landscape of the taiga to matter-of-fact grumbles about the inefficiency of his stove, from accounts of the brutal conditions of the camp to reflections on the cruelty of loneliness, this diary is an astonishing record—a visceral and immediate description of a place and time whose repercussions still affect the shape of modern Russia, and modern Europe.

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Page Count

205

Publisher

Simon and Schuster

Published Date

ISBN 10

1681774976

ISBN 13

9781681774978

Wireless Sensor and Actuator Networks

Algorithms and Protocols for Scalable Coordination and Data Communication

By: Amiya Nayak,Ivan Stojmenovic

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Wireless Sensor and Actuator Networks

Algorithms and Protocols for Scalable Coordination and Data Communication

By: Amiya Nayak,Ivan Stojmenovic

This timely book offers a mixture of theory, experiments, and simulations that provides qualitative and quantitative insights in the field of sensor and actuator networking. The chapters are selected in a way that makes the book comprehensive and self-contained. It covers a wide range of recognized problems in sensor networks, striking a balance between theoretical and practical coverage. The book is appropriate for graduate students and practitioners working as engineers, programmers, and technologists.

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Page Count

316

Publisher

John Wiley & Sons

Published Date

ISBN 10

0470570504

ISBN 13

9780470570500

3D User Interfaces

Theory and Practice

By: Joseph J. LaViola Jr.,Ernst Kruijff,Ryan P. McMahan,Doug Bowman,Ivan P. Poupyrev

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3D User Interfaces

Theory and Practice

By: Joseph J. LaViola Jr.,Ernst Kruijff,Ryan P. McMahan,Doug Bowman,Ivan P. Poupyrev

The Complete, Up-To-Date Guide to Building Great 3D User Interfaces for Any Application 3D interaction is suddenly everywhere. But simply using 3D input or displays isn’t enough: 3D interfaces must be carefully designed for optimal user experience. 3D User Interfaces: Theory and Practice, Second Edition is today’s most comprehensive primary reference to building state-of-the-art 3D user interfaces and interactions. Five pioneering researchers and practitioners cover the full spectrum of emerging applications, techniques, and best practices. The authors combine theoretical foundations, analysis of leading devices, and empirically validated design guidelines. This edition adds two new chapters on human factors and general human-computer interaction—indispensable foundational knowledge for building any 3D user interface. It also demonstrates advanced concepts at work through two running case studies: a first-person VR game and a mobile augmented reality application. Coverage Includes 3D user interfaces: evolution, elements, and roadmaps Key applications: virtual and augmented reality (VR, AR), mobile/wearable devices What 3D UI designers should know about human sensory systems and cognition ergonomics How proven human-computer interaction techniques apply to 3D UIs 3D UI output hardware for visual, auditory, and haptic/ tactile systems Obtaining 3D position, orientation, and motion data for users in physical space 3D object selection and manipulation Navigation and wayfinding techniques for moving through virtual and physical spaces Changing application state with system control techniques, issuing commands, and enabling other forms of user input Strategies for choosing, developing, and evaluating 3D user interfaces Utilizing 2D, “magic,” “natural,” multimodal, and two-handed interaction The future of 3D user interfaces: open research problems and emerging technologies

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884

Publisher

Addison-Wesley Professional

Published Date

ISBN 10

0134034465

ISBN 13

9780134034461

Theory of Stellar Atmospheres

An Introduction to Astrophysical Non-equilibrium Quantitative Spectroscopic Analysis

By: Ivan Hubeny,Dimitri Mihalas

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Theory of Stellar Atmospheres

An Introduction to Astrophysical Non-equilibrium Quantitative Spectroscopic Analysis

By: Ivan Hubeny,Dimitri Mihalas

The most authoritative synthesis of the quantitative spectroscopic analysis of stellar atmospheres This book provides an in-depth and self-contained treatment of the latest advances achieved in quantitative spectroscopic analyses of the observable outer layers of stars and similar objects. Written by two leading researchers in the field, it presents a comprehensive account of both the physical foundations and numerical methods of such analyses. The book is ideal for astronomers who want to acquire deeper insight into the physical foundations of the theory of stellar atmospheres, or who want to learn about modern computational techniques for treating radiative transfer in non-equilibrium situations. It can also serve as a rigorous yet accessible introduction to the discipline for graduate students. Provides a comprehensive, up-to-date account of the field Covers computational methods as well as the underlying physics Serves as an ideal reference book for researchers and a rigorous yet accessible textbook for graduate students An online illustration package is available to professors at press.princeton.edu

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Page Count

945

Publisher

Princeton University Press

Published Date

ISBN 10

1400852730

ISBN 13

9781400852734

Top Gear: Motor Mania

By: Ivan Berg,Nik Berg

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Top Gear: Motor Mania

By: Ivan Berg,Nik Berg

Did you know that Jasons and Tracies crash more cars than Jacquelines and Damons? Or that a boomerang can be used to repair a knackered clutch? Have you ever wanted to visit a naked car show, wondered what it's like to drive on the world's most dangerous road, or receive the world's most expensive speeding ticket? Want to read about flying cars, amphibious cars, or atomic cars? What about the Accord that can actually strike a chord, or the love car park? Dip inside to find all these plus stacks of other stuff, including cars in films, cars on TV, cars in songs - even cars as coffins. Top Gear: Motor Mania is a car book like no other. It's full of the strangest stories, fascinating facts and spectacular stats - a must for any car nut.

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Page Count

194

Publisher

Random House

Published Date

ISBN 10

140904730X

ISBN 13

9781409047308

3D User Interfaces

Theory and Practice

By: Doug Bowman,Ernst Kruijff,Joseph J. LaViola Jr.,Ivan P. Poupyrev

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3D User Interfaces

Theory and Practice

By: Doug Bowman,Ernst Kruijff,Joseph J. LaViola Jr.,Ivan P. Poupyrev

Here’s what three pioneers in computer graphics and human-computer interaction have to say about this book: “What a tour de force—everything one would want—comprehensive, encyclopedic, and authoritative.” — Jim Foley “At last, a book on this important, emerging area. It will be an indispensable reference for the practitioner, researcher, and student interested in 3D user interfaces.” — Andy van Dam “Finally, the book we need to bridge the dream of 3D graphics with the user-centered reality of interface design. A thoughtful and practical guide for researchers and product developers. Thorough review, great examples.” — Ben Shneiderman As 3D technology becomes available for a wide range of applications, its successful deployment will require well-designed user interfaces (UIs). Specifically, software and hardware developers will need to understand the interaction principles and techniques peculiar to a 3D environment. This understanding, of course, builds on usability experience with 2D UIs. But it also involves new and unique challenges and opportunities. Discussing all relevant aspects of interaction, enhanced by instructive examples and guidelines, 3D User Interfaces comprises a single source for the latest theory and practice of 3D UIs. Many people already have seen 3D UIs in computer-aided design, radiation therapy, surgical simulation, data visualization, and virtual-reality entertainment. The next generation of computer games, mobile devices, and desktop applications also will feature 3D interaction. The authors of this book, each at the forefront of research and development in the young and dynamic field of 3D UIs, show how to produce usable 3D applications that deliver on their enormous promise. Coverage includes: The psychology and human factors of various 3D interaction tasks Different approaches for evaluating 3D UIs Results from empirical studies of 3D interaction techniques Principles for choosing appropriate input and output devices for 3D systems Details and tips on implementing common 3D interaction techniques Guidelines for selecting the most effective interaction techniques for common 3D tasks Case studies of 3D UIs in real-world applications To help you keep pace with this fast-evolving field, the book’s Web site, www.3dui.org, will offer information and links to the latest 3D UI research and applications.

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Page Count

867

Publisher

Addison-Wesley

Published Date

ISBN 10

013339056X

ISBN 13

9780133390568

Large-Scale Scientific Computing

6th International Conference, LSSC 2007, Sozopol, Bulgaria, June 5-9, 2007, Revised Papers

By: Ivan Lirkov,Svetozar Margenov

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Large-Scale Scientific Computing

6th International Conference, LSSC 2007, Sozopol, Bulgaria, June 5-9, 2007, Revised Papers

By: Ivan Lirkov,Svetozar Margenov

This book constitutes the thoroughly refereed post-conference proceedings of the 6th International Conference on Large-Scale Scientific Computations, LSSC 2007, held in Sozopol, Bulgaria, in June 2007. The 81 revised full papers presented together with 5 invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on robust multilevel and hierarchical preconditioning methods; monte carlo: tools, applications, distributed computing; operator splittings, their application and realization; recent advances in methods and applications for large scale computations and optimization of coupled engineering problems; control systems; environmental modelling; computational grid and large-scale problems; application of metaheuristics to large-scale problems; and contributed talks.

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Page Count

754

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3540788255

ISBN 13

9783540788256

Fiendishly Frustrating Brain-Twisting Puzzles

By: Ivan Moscovich

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Fiendishly Frustrating Brain-Twisting Puzzles

By: Ivan Moscovich

Jumping Coins, Cubes and Routes, Find the Polygons, and Distortrix: these are just a few of the incredible brain-twisting conundrums in this colorful, super-fun compilation by puzzle whiz Ivan Moscovich. Sample games give a hint of what's to come and prime your mind for the challenges you'll face. Inside a hexagon, a continuous path connects 19 different nodes: find that trail, navigating a series of pointing arrows and visiting each node only once. On the Rebound features tricky little problems involving a pool ball on a table and the best way to shoot it. A Piece of Cake is no piece of cake: arrange the segments so that no two colored or numbered ones touch another of the same color or number. You'll think your brain really is twisted once you solve all of these.

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Page Count

134

Publisher

Sterling Publishing Company, Inc.

Published Date

ISBN 10

1402718098

ISBN 13

9781402718090

Learning Genetic Algorithms with Python

Empower the performance of Machine Learning and AI models with the capabilities of a powerful search algorithm (English Edition)

By: Ivan Gridin

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Learning Genetic Algorithms with Python

Empower the performance of Machine Learning and AI models with the capabilities of a powerful search algorithm (English Edition)

By: Ivan Gridin

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Solve jigsaw puzzle

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Page Count

330

Publisher

BPB Publications

Published Date

ISBN 10

8194837758

ISBN 13

9788194837756

Book's by Ivan Gridin

Learning Genetic Algorithms with Python

Learning Genetic Algorithms with Python

Time Series Forecasting using Deep Learning

Time Series Forecasting using Deep Learning

Practical Deep Reinforcement Learning with Python

Practical Deep Reinforcement Learning with Python

Practical Deep Reinforcement Learning with Python

Practical Deep Reinforcement Learning with Python

The Day Will Pass Away

The Day Will Pass Away

Wireless Sensor and Actuator Networks

Wireless Sensor and Actuator Networks

3D User Interfaces

3D User Interfaces

Theory of Stellar Atmospheres

Theory of Stellar Atmospheres

Top Gear: Motor Mania

Top Gear: Motor Mania

3D User Interfaces

3D User Interfaces

Large-Scale Scientific Computing

Large-Scale Scientific Computing

Fiendishly Frustrating Brain-Twisting Puzzles

Fiendishly Frustrating Brain-Twisting Puzzles

Learning Genetic Algorithms with Python

Learning Genetic Algorithms with Python

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