Machine Learning Guide for Oil and Gas Using Python: A Step-By-Step Breakdown with Data, Algorithms, Codes, and Applications, Belyadi Hoss, Haghighat Alireza
Описание: This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly.
IoT Machine Learning Applications in Telecom, Energy, and Agriculture
CHAPTER 1: Getting Started: Software and Hardware Needed
CHAPTER 2: Overview of IoT and IIoT
CHAPTER 3: Using Machine Learning with IoT and IIoT in Python
CHAPTER 4: Using Machine Learning and IoT in Telecom, Energy, and Agriculture
CHAPTER 5: Preparing for the Case Studies
CHAPTER 6: Configuring IIoT Energy Meter
CHAPTER 7: Telecom Industry Case Study: Solving the Problem of Call Drops with IoT
CHAPTER 8: Energy Industry Case Study: Predictive Maintenance for an Industrial Machine
CHAPTER 9: Agriculture Industry Case Study: Predicting a Cash Crop Yield
Название: Machine Learning Applications Using Python ISBN: 1484237862 ISBN-13(EAN): 9781484237861 Издательство: Springer Рейтинг: Цена: 9146.00 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.
Описание: This book will get you to grips with the Spark Python API. You`ll explore how Python can be used with Spark to build scalable and reliable data-intensive applications.
Автор: Subasi, Abdulhamit Название: Practical Machine Learning For Data Analysis Using Python ISBN: 0128213795 ISBN-13(EAN): 9780128213797 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.
Описание: This book provides an introduction to reservoir simulation, by a simulator developer. It contains a large number of numerical examples, which come fully equipped with online open-source code, allowing the reader to reproduce results and experiment with their own work. This title is also available as Open Access on Cambridge Core.
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