Keras Reinforcement Learning Projects, Ciaburro Giuseppe
Автор: Ciaburro Giuseppe Название: Hands-On Reinforcement Learning with R ISBN: 1789616719 ISBN-13(EAN): 9781789616712 Издательство: Неизвестно Рейтинг: Цена: 6206.00 р. Наличие на складе: Нет в наличии.
Описание: Reinforcement Learning is an exciting part of machine learning. It has uses in technology from autonomous cars to game playing, and creates algorithms that can adapt to environmental changes. This book helps to understand how to implement RL with R, and explores interesting practical examples, such as using tabular Q-learning to control robots.
Автор: Venkateswaran Balaji, Ciaburro Giuseppe Название: Neural Networks with R ISBN: 1788397878 ISBN-13(EAN): 9781788397872 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning explores the study and construction of algorithms that can learn from, and make predictions on, data. This book will act as an entry point for anyone who wants to make a career in the field of Machine Learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-M..
Автор: Giuseppe Ciaburro Название: MATLAB for Machine Learning ISBN: 1788398432 ISBN-13(EAN): 9781788398435 Издательство: Неизвестно Рейтинг: Цена: 10114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will build a foundation for machine learning using MATLAB for beginners. It will also help you learn regression, clustering, classification, predictive analytics, artificial neural networks, and more with MATLAB.
Автор: Ciaburro Giuseppe Название: Keras 2.x Projects ISBN: 1789536642 ISBN-13(EAN): 9781789536645 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Keras is a deep learning library that enables the fast, efficient training of deep learning models. The book begins with setting up the environment, training various types of models in the domain of deep learning and reinforcement learning. The projects are exciting and are real-world market demanding projects which take you from simple to ...
Автор: Ciaburro Giuseppe, Joshi Prateek Название: Python Machine Learning Cookbook - Second Edition ISBN: 1789808456 ISBN-13(EAN): 9781789808452 Издательство: Неизвестно Рейтинг: Цена: 7171.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With this book, you will learn how to perform various machine learning tasks in different environments. You`ll use a wide variety of machine learning algorithms using Python to solve real-world problems. By the end of the book, you will learn to implement most used machine learning algorithms using complex datasets and optimized techniques.
Автор: Perrier Alexis, Ayyadevara Kishore, Ciaburro Giuseppe Название: Hands-On Machine Learning on Google Cloud Platform ISBN: 1788393481 ISBN-13(EAN): 9781788393485 Издательство: Неизвестно Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, you will learn how to create powerful machine learning based applications for a wide variety of problems leveraging different data services from the Google Cloud Platform. Finally, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems.
Автор: Ciaburro Giuseppe Название: Regression Analysis with R ISBN: 178862730X ISBN-13(EAN): 9781788627306 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Regression analysis is a statistical process which enables prediction of relationships between variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move ...
Enhance your simulation modeling skills by creating and analyzing digital prototypes of a physical model using Python programming with this comprehensive guide
Key Features
Learn to create a digital prototype of a real model using hands-on examples
Evaluate the performance and output of your prototype using simulation modeling techniques
Understand various statistical and physical simulations to improve systems using Python
Book Description
Simulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world. With this comprehensive guide, you'll understand various computational statistical simulations using Python.
Starting with the fundamentals of simulation modeling, you'll understand concepts such as randomness and explore data generating processes, resampling methods, and bootstrapping techniques. You'll then cover key algorithms such as Monte Carlo simulations and Markov decision processes, which are used to develop numerical simulation models, and discover how they can be used to solve real-world problems. As you advance, you'll develop simulation models to help you get accurate results and enhance decision-making processes. Using optimization techniques, you'll learn to modify the performance of a model to improve results and make optimal use of resources. The book will guide you in creating a digital prototype using practical use cases for financial engineering, prototyping project management to improve planning, and simulating physical phenomena using neural networks.
By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.
What you will learn
Gain an overview of the different types of simulation models
Get to grips with the concepts of randomness and data generation process
Understand how to work with discrete and continuous distributions
Work with Monte Carlo simulations to calculate a definite integral
Find out how to simulate random walks using Markov chains
Obtain robust estimates of confidence intervals and standard errors of population parameters
Discover how to use optimization methods in real-life applications
Run efficient simulations to analyze real-world systems
Who this book is for
Hands-On Simulation Modeling with Python is for simulation developers and engineers, model designers, and anyone already familiar with the basic computational methods that are used to study the behavior of systems. This book will help you explore advanced simulation techniques such as Monte Carlo methods, statistical simulations, and much more using Python. Working knowledge of Python programming language is required.
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