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Machine Learning with Python, Tarkeshwar Barua


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Автор: Tarkeshwar Barua
Название:  Machine Learning with Python
ISBN: 9783110697162
Издательство: Walter de Gruyter
Классификация:

ISBN-10: 3110697165
Обложка/Формат: Paperback
Страницы: 358
Вес: 0.54 кг.
Дата издания: 09.08.2024
Серия: De gruyter stem
Язык: English
Иллюстрации: 100 illustrations, black and white; 30 tables, black and white
Размер: 170 x 240 x 29
Читательская аудитория: Postgraduate, research & scholarly
Ключевые слова: Algorithms & data structures,Artificial intelligence,Computer programming / software development,Computer science,Software Engineering, COMPUTERS / Artificial Intelligence / General,COMPUTERS / Programming / Algorithms,COMPUTERS / Programming / General,COMPUTERS / Software Development & Engineering / General
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Поставляется из: Германии
Описание:

This book explains how to use the programming language Python to develop machine learning and deep learning tasks.




Learning Python, 5 ed.

Автор: Lutz Mark
Название: Learning Python, 5 ed.
ISBN: 1449355730 ISBN-13(EAN): 9781449355739
Издательство: Wiley
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Цена: 9502.00 р.
Наличие на складе: Поставка под заказ.

Описание: Based on author Mark Lutz`s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It`s an ideal way to begin, whether you`re new to programming or a professional developer versed in other languages.

Introduction to Machine Learning with Python

Автор: Guido Sarah
Название: Introduction to Machine Learning with Python
ISBN: 1449369413 ISBN-13(EAN): 9781449369415
Издательство: Wiley
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Цена: 9502.00 р.
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Описание: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.

Building Machine Learning Systems with Python

Автор: Chaffer J
Название: Building Machine Learning Systems with Python
ISBN: 1782161406 ISBN-13(EAN): 9781782161400
Издательство: Неизвестно
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Цена: 10114.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need.

Key Features

  • Master Machine Learning using a broad set of Python libraries and start building your own Python-based ML systems
  • Covers classification, regression, feature engineering, and much more guided by practical examples
  • A scenario-based tutorial to get into the right mind-set of a machine learner (data exploration) and successfully implement this in your new or existing projects

Book Description

Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.

Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail.

Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques.

Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.


Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.

Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.

What you will learn

  • Build a classification system that can be applied to text, images, or sounds
  • Use scikit-learn, a Python open-source library for machine learning
  • Explore the mahotas library for image processing and computer vision
  • Build a topic model of the whole of Wikipedia
  • Get to grips with recommendations using the basket analysis
  • Use the Jug package for data analysis
  • Employ Amazon Web Services to run analyses on the cloud
  • Recommend products to users based on past purchases
Designing Machine Learning Systems with Python

Автор: David Julian
Название: Designing Machine Learning Systems with Python
ISBN: 1785882953 ISBN-13(EAN): 9781785882951
Издательство: Неизвестно
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Цена: 9010.00 р.
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Python Machine Learning Case Studies

Автор: Danish Haroon
Название: Python Machine Learning Case Studies
ISBN: 1484228227 ISBN-13(EAN): 9781484228227
Издательство: Springer
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Цена: 5309.00 р.
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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
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Цена: 12137.00 р.
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.

Monetizing Machine Learning: Quickly Turn Python ML Ideas Into Web Applications on the Serverless Cloud

Автор: Amunategui Manuel, Roopaei Mehdi
Название: Monetizing Machine Learning: Quickly Turn Python ML Ideas Into Web Applications on the Serverless Cloud
ISBN: 1484238729 ISBN-13(EAN): 9781484238721
Издательство: Springer
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Цена: 10480.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book--Amazon, Microsoft, Google, and PythonAnywhere.

You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time.

Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serverless cloud provider. You can easily jump to or skip particular topics in the book. You also will have access to Jupyter notebooks and code repositories for complete versions of the code covered in the book.

What You'll Learn

  • Extend your machine learning models using simple techniques to create compelling and interactive web dashboards
  • Leverage the Flask web framework for rapid prototyping of your Python models and ideas
  • Create dynamic content powered by regression coefficients, logistic regressions, gradient boosting machines, Bayesian classifications, and more
  • Harness the power of TensorFlow by exporting saved models into web applications
  • Create rich web dashboards to handle complex real-time user input with JavaScript and Ajax to yield interactive and tailored content
  • Create dashboards with paywalls to offer subscription-based access
  • Access API data such as Google Maps, OpenWeather, etc.
  • Apply different approaches to make sense of text data and return customized intelligence
  • Build an intuitive and useful recommendation site to add value to users and entice them to keep coming back
  • Utilize the freemium offerings of Google Analytics and analyze the results
  • Take your ideas all the way to your customer's plate using the top serverless cloud providers

Who This Book Is For

Those with some programming experience with Python, code editing, and access to an interpreter in working order. The book is geared toward entrepreneurs who want to get their ideas onto the web without breaking the bank, small companies without an IT staff, students wanting exposure and training, and for all data science professionals ready to take things to the next level.

Machine Learning Applications Using Python

Название: Machine Learning Applications Using Python
ISBN: 1484237862 ISBN-13(EAN): 9781484237861
Издательство: Springer
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Цена: 10480.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:
Part 1: HealthcareChapter 1. Overview of machine learning in healthcare.Chapter 2. Key technological advancements in healthcare.Chapter 3. How to implement machine learning in healthcare.Chapter 4. Case studies on how organizations are changing the game in the market.Chapter 5. Pitfalls to avoid while implementing machine learning in healthcare.Chapter 6. Healthcare specific innovative Ideas for monetizing machine learning.
Part 2: Retail Chapter 7. Overview of machine learning in Retail.Chapter 8. Key technological advancements in Retail.Chapter 9. How to implement machine learning in Retail.Chapter 10. Case studies on how organizations are changing the game in the market. c. One discussion based case study. d. One practical case study with Python code.Chapter 11. Pitfalls to avoid while implementing machine learning in retail.Chapter 12. Retail specific innovative Ideas for monetizing machine learning.
Part 3: Finance Chapter 13. Overview of machine learning in Finance.Chapter 14. Key technological advancements in Finance.Chapter 15. How to implement machine learning in Finance.Chapter 16. Case studies on how organizations are changing the game in the market. e. One discussion based case study. f. One practical case study with Python code.Chapter 17. Pitfalls to avoid while implementing machine learning in Finance.Chapter 18. Finance specific innovative Ideas for monetizing machine learning.

Python Machine Learning by Example

Автор: (Hayden) Liu Yuxi
Название: Python Machine Learning by Example
ISBN: 1789616727 ISBN-13(EAN): 9781789616729
Издательство: Неизвестно
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Цена: 7171.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Python Machine Learning by Example covers in detail the most important concepts, techniques, algorithms, and libraries that every data scientist or machine learning practitioner needs to know. This example-enriched guide will make your learning journey easier and happier, enabling you to solve real-world data-driven problems.

Python Machine Learning, Third Edition

Автор: Raschka Sebastian, Mirjalili Vahid
Название: Python Machine Learning, Third Edition
ISBN: 1789955750 ISBN-13(EAN): 9781789955750
Издательство: Неизвестно
Рейтинг:
Цена: 10114.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. This new third edition is updated for TensorFlow 2 and the latest additions to ...

Python 3 for Machine Learning

Автор: Campesato Oswald
Название: Python 3 for Machine Learning
ISBN: 1683924959 ISBN-13(EAN): 9781683924951
Издательство: Неизвестно
Цена: 7166.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Provides the reader with basic Python3 programming concepts related to machine learning. Chapters provide an introduction to Python 3, NumPy, and Pandas; introduce the fundamental concepts of machine learning; cover machine learning classifiers, such as logistic regression and k-NN; and explore NLP and RL.

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
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Цена: 6986.00 р.
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

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