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Machine Learning with Python, Zollanvari, Amin


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Цена: 47810T
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Автор: Zollanvari, Amin   (Амин Золланвари)
Название:  Machine Learning with Python   (Амин Золланвари: Машинное обучение с Python)
Издательство: Springer
Классификация:
ISBN: 3031333411
ISBN-13(EAN): 9783031333415
Обложка/Формат: Hardback
Дата издания: 26.07.2023
Язык: English
Рейтинг:
Поставляется из: Германии
Описание: This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made based on one criterion: whether the practical utility of a certain method justifies its theoretical elaboration for students with a typical mathematical background in engineering and other quantitative fields. As a result, not only does the book contain practically useful techniques, it also presents them in a mathematical language that is accessible to both graduate and advanced undergraduate students. The textbook covers a range of topics including nearest neighbors, linear models, decision trees, ensemble learning, model evaluation and selection, dimensionality reduction, assembling various learning stages, clustering, and deep learning along with an introduction to fundamental Python packages for data science and machine learning such as NumPy, Pandas, Matplotlib, Scikit-Learn, XGBoost, and Keras with TensorFlow backend. Given the current dominant role of the Python programming language for machine learning, the book complements the theoretical presentation of each technique by its Python implementation. In this regard, two chapters are devoted to cover necessary Python programming skills. This feature makes the book self-sufficient for students with different programming backgrounds and is in sharp contrast with other books in the field that assume readers have prior Python programming experience. As such, the systematic structure of the book, along with the many examples and exercises presented, will help the readers to better grasp the content and be equipped with the practical skills required in day-to-day machine learning applications.
Дополнительное описание: Preface.- About This Book.- 1. Introduction.- 2. Getting Started with Python.- 3. Three Fundamental Python Packages.- 4. Supervised Learning in Practice: The First Application Using Scikit-Learn. - 5. K-Nearest Neighbors.- 6. Linear Models.- 7. Decision T


Mathematics for Machine Learning

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
Рейтинг:
Цена: 33340 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Deep Learning

Автор: Goodfellow Ian, Bengio Yoshua, Courville Aaron
Название: Deep Learning
ISBN: 0262035618 ISBN-13(EAN): 9780262035613
Издательство: MIT Press
Рейтинг:
Цена: 71280 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.

"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject."
-- Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.

The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.

Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.


Machine Learning Guide for Oil and Gas Using Python: A Step-By-Step Breakdown with Data, Algorithms, Codes, and Applications

Автор: Belyadi Hoss, Haghighat Alireza
Название: Machine Learning Guide for Oil and Gas Using Python: A Step-By-Step Breakdown with Data, Algorithms, Codes, and Applications
ISBN: 0128219297 ISBN-13(EAN): 9780128219294
Издательство: Elsevier Science
Рейтинг:
Цена: 101950 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges.


Machine learning in the oil and gas industry

Автор: Yogendra Narayan Pandey et al
Название: Machine learning in the oil and gas industry
ISBN: 1484260937 ISBN-13(EAN): 9781484260937
Издательство: Springer
Рейтинг:
Цена: 33090 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches.

The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.

Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will LearnUnderstanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industryGet the basic concepts of computer programming and machine and deep learning required for implementing the algorithms usedStudy interesting industry problems that are good candidates for being solved by machine and deep learningDiscover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.


Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems

Автор: Geron Aurelien
Название: Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems
ISBN: 1492032646 ISBN-13(EAN): 9781492032649
Издательство: Wiley
Рейтинг:
Цена: 50010 T
Наличие на складе: Поставка под заказ.
Описание:

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.

The updated edition of this practical book uses concrete examples, minimal theory, and three 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. 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.


Practical Machine Learning with Python

Автор: Dipanjan Sarkar; Raghav Bali; Tushar Sharma
Название: Practical Machine Learning with Python
ISBN: 1484232062 ISBN-13(EAN): 9781484232064
Издательство: Springer
Рейтинг:
Цена: 36770 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully.

Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code.

Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered.

Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment.

Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem.

Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today

What You'll Learn

  • Execute end-to-end machine learning projects and systems
  • Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks
  • Review case studies depicting applications of machine learning and deep learning on diverse domains and industries
  • Apply a wide range of machine learning models including regression, classification, and clustering.
  • Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning.

Who This Book Is For
IT professionals, analysts, developers, data scientists, engineers, graduate students

Python Programming Crash Course: A Beginners to Learn Python Computer Language .Introduction to Machine Learning and Artificial Intelligence

Автор: Treu Peter
Название: Python Programming Crash Course: A Beginners to Learn Python Computer Language .Introduction to Machine Learning and Artificial Intelligence
ISBN: 1801449821 ISBN-13(EAN): 9781801449823
Издательство: Неизвестно
Рейтинг:
Цена: 25570 T
Наличие на складе: Нет в наличии.
Описание:

Do you Want to learn more about Python Programming, Machine Learning and Artificial Intelligence ?.... then read on.

Python is a powerful programming language that can be used for the development of various types of applications. It is an Object-Oriented Programming language and it is interpreted rather than being compiled.

Python is considered to be among the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also some of the major attractions for this language. Programmers are now developing a wide range of mobile as well as web applications that we enjoy on an everyday basis.

Python Programming Crash Course doesn't make any assumptions about your background or knowledge of Python or computer programming. You need no prior knowledge to benefit from this book. You will be guided step by step using a logical and systematic approach. As new concepts, commands, or jargon are encountered they are explained in plain language, making it easy for anyone to understand.

In this Book you will learning:

  • Introduction ito iPython
  • Variables
  • Operators
  • Loops
  • Functions
  • Object-Oriented iProgramming-OOP
  • Modules
  • File ihandling

Would you like to know more?


Download the Book, Python Programming Crash Course .Scroll to the top of the page and click the "Buy now" button to get your copy now.



Machine Learning for Absolute Beginners: A Plain English Introduction (Third Edition)

Автор: Theobald, Oliver
Название: Machine Learning for Absolute Beginners: A Plain English Introduction (Third Edition)
ISBN: ISBN-13(EAN): 9798558098426
Издательство: Неизвестно
Рейтинг:
Цена: 15260 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guid

Автор: Academy Computer Programming
Название: Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guid
ISBN: 1914185099 ISBN-13(EAN): 9781914185090
Издательство: Неизвестно
Рейтинг:
Цена: 19760 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Inside this book you will find all the basic notions to start with Python and all the programming concepts to build machine learning models. With our proven strategies you will write efficient Python codes in less than a week!


Python Machine Learning Case Studies

Автор: Danish Haroon
Название: Python Machine Learning Case Studies
ISBN: 1484228227 ISBN-13(EAN): 9781484228227
Издательство: Springer
Рейтинг:
Цена: 27940 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources.
Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You'll see machine learning techniques that you can use to support your products and services. Moreover you'll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs.
By taking a step-by-step approach to coding in Python you'll be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems.
What You Will Learn

  • Gain insights into machine learning concepts
  • Work on real-world applications of machine learning
  • Learn concepts of model selection and optimization
  • Get a hands-on overview of Python from a machine learning point of view

Who This Book Is For
Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.


Python machine learning cookbook

Автор: Joshi, Prateek
Название: Python machine learning cookbook
ISBN: 1786464470 ISBN-13(EAN): 9781786464477
Издательство: Неизвестно
Рейтинг:
Цена: 72590 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Explore various real-life scenarios where you can use machine learning. With the help of practical examples, this cookbook will help you to understand which algorithms to use in a given context.

Building Machine Learning Systems with Python - Second Edition

Автор: Richert Willi
Название: Building Machine Learning Systems with Python - Second Edition
ISBN: 1784392774 ISBN-13(EAN): 9781784392772
Издательство: Неизвестно
Цена: 41240 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Get more from your data with the power of Python machine learning systems

Key Features

  • Build your own Python-based machine learning systems tailored to solve any problem
  • Discover how Python offers a multiple context solution for create machine learning systems
  • Practical scenarios using the key Python machine learning libraries to successfully implement in your projects

Book Description

Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python is a wonderful language to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation. With its excellent collection of open source machine learning libraries you can focus on the task at hand while being able to quickly try out many ideas.

This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and introducing libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling, creating recommendation systems. Later on, the book covers advanced topics such as topic modeling, basket analysis, and cloud computing. These will extend your abilities and enable you to create large complex systems.

With this book, you gain the tools and understanding required to build your own systems, tailored to solve your real-world data analysis problems.

What you will learn

  • Build a classification system that can be applied to text, images, or sounds
  • Use NumPy, SciPy, scikit-learn - scientific Python open source libraries for scientific computing and machine learning
  • Explore the mahotas library for image processing and computer vision
  • Build a topic model for the whole of Wikipedia
  • Employ Amazon Web Services to run analysis on the cloud
  • Debug machine learning problems
  • Get to grips with recommendations using basket analysis
  • Recommend products to users based on past purchases


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