Learning Geospatial Analysis with Python, Joel Lawhead
Автор: Chollet Francois Название: Deep Learning with Python ISBN: 1617294438 ISBN-13(EAN): 9781617294433 Издательство: Pearson Education Рейтинг: Цена: 7918.00 р. Наличие на складе: Поставка под заказ.
Описание:
Summary
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Francois Chollet, this book builds your understanding through intuitive explanations and practical examples.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning--a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.
About the Book
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Francois Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
What's Inside
Deep learning from first principles
Setting up your own deep-learning environment
Image-classification models
Deep learning for text and sequences
Neural style transfer, text generation, and image generation
About the Reader
Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.
About the Author
Francois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.
Table of Contents
PART 1 - FUNDAMENTALS OF DEEP LEARNING
What is deep learning?
Before we begin: the mathematical building blocks of neural networks
Getting started with neural networks
Fundamentals of machine learning
PART 2 - DEEP LEARNING IN PRACTICE
Deep learning for computer vision
Deep learning for text and sequences
Advanced deep-learning best practices
Generative deep learning
Conclusions
appendix A - Installing Keras and its dependencies on Ubuntuappendix B - Running Jupyter notebooks on an EC2 GPU instance
Описание: Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.What You’ll Learn Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions. Design, develop, train, validate, and deploy deep neural networks using the Keras framework Use best practices for debugging and validating deep learning models Deploy and integrate deep learning as a service into a larger software service or product Extend deep learning principles into other popular frameworks Who This Book Is For Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.
Автор: Michael Diener Название: Python Geospatial Analysis Cookbook ISBN: 1783555076 ISBN-13(EAN): 9781783555079 Издательство: Amazon Internet Рейтинг: Цена: 10114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Название: Machine Learning Applications Using Python ISBN: 1484237862 ISBN-13(EAN): 9781484237861 Издательство: Springer Рейтинг: 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.
Автор: Miller Preston, Bryce Chapin Название: Learning Python for Forensics ISBN: 1783285230 ISBN-13(EAN): 9781783285235 Издательство: Неизвестно Цена: 12137.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learn the art of designing, developing, and deploying innovative forensic solutions through Python
Key Features
This practical guide will help you solve forensic dilemmas through the development of Python scripts
Analyze Python scripts to extract metadata and investigate forensic artifacts
Master the skills of parsing complex data structures by taking advantage of Python libraries
Book Description
This book will illustrate how and why you should learn Python to strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. The tutorials use an interactive design, giving you experience of the development process so you gain a better understanding of what it means to be a forensic developer.
Each chapter walks you through a forensic artifact and one or more methods to analyze the evidence. It also provides reasons why one method may be advantageous over another. We cover common digital forensics and incident response scenarios, with scripts that can be used to tackle case work in the field. Using built-in and community-sourced libraries, you will improve your problem solving skills with the addition of the Python scripting language. In addition, we provide resources for further exploration of each script so you can understand what further purposes Python can serve. With this knowledge, you can rapidly develop and deploy solutions to identify critical information and fine-tune your skill set as an examiner.
What you will learn
Discover how to perform Python script development
Update yourself by learning the best practices in forensic programming
Build scripts through an iterative design
Explore the rapid development of specialized scripts
Understand how to leverage forensic libraries developed by the community
Design flexibly to accommodate present and future hurdles
Conduct effective and efficient investigations through programmatic pre-analysis
Discover how to transform raw data into customized reports and visualizations
Автор: Hill Название: Learning Scientific Programming with Python ISBN: 1107075416 ISBN-13(EAN): 9781107075412 Издательство: Cambridge Academ Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn to master basic programming tasks from scratch with real-life scientific examples drawn from many different areas of science and engineering. This complete introduction to using Python teaches Numpy, SciPy and Matplotlib libraries and is supported by extensive online resources to provide a targeted package for students and researchers.
Автор: Joshi, Prateek Название: Python machine learning cookbook ISBN: 1786464470 ISBN-13(EAN): 9781786464477 Издательство: Неизвестно Рейтинг: 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.
Автор: Danish Haroon Название: Python Machine Learning Case Studies ISBN: 1484228227 ISBN-13(EAN): 9781484228227 Издательство: Springer Рейтинг: Цена: 5309.00 р. 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.
Автор: Matt A. Wood Название: Python and Matplotlib Essentials for Scientists and Engineers ISBN: 1681749106 ISBN-13(EAN): 9781681749105 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 6237.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an introduction to the core features of the Python programming language and Matplotlib plotting routings for scientists and engineers (or students of either discipline) who want to use Python™ to analyse data, simulate physical processes, and render publication-quality plots. No previous programming experience is needed before reading the first page.Readers will learn the core features of the Python programming language in under a day. They will be able to immediately use Python to implement codes that solve their own problems and make beautiful plots and animations. Python code is extremely fast to prototype, allowing users to achieve results quickly and accurately. The examples within the book are available for download.Python and Matplotlib Essentials for Scientists and Engineers is accessible for motivated high-school students, but will likely be most useful for undergraduate and graduate students as well as working professionals who have some background with the basic mathematical concepts. This book is intended for technical people who want to get things done.
Автор: Dipanjan Sarkar; Raghav Bali; Tushar Sharma Название: Practical Machine Learning with Python ISBN: 1484232062 ISBN-13(EAN): 9781484232064 Издательство: Springer Рейтинг: 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
Автор: Manaswi, Navin Kumar Название: Deep learning with applications using python ISBN: 1484235150 ISBN-13(EAN): 9781484235157 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers intermediate and advanced levels of deep learning, including convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. What You Will Learn
Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn.
Build face recognition and face detection capabilities
Create speech-to-text and text-to-speech functionality
Make chatbots using deep learning
Who This Book Is For Data scientists and developers who want to adapt and build deep learning applications.
Are you excited about Artificial Intelligence and want to get started?Are you excited about Machine Learning and want to learn how to implement in Python?
The book below is the answer.
Given the large amounts of data we use everyday; whether it is in the web, supermarkets, social media etc. analysis of data has become integral to our daily life. The ability to do so effectively can propel your career or business to great heights. Machine Learning is the most effective data analysis tool. While it is a complex topic, it can be broken down into simpler steps, as show in this book. We are using Python, which is a great programming language for beginners.
Python is a great language that is commonly used with Machine Learning. Python is used extensively in Mathematics, Gaming and Graphic Design. It is fast to develop and prototype. It is web capable, meaning that we can use Python to gather web data. It is adaptable, and has great community of users.
Here's What's Included In This Book:
What is Machine Learning?
Why use Python?
Regression Analysis using Python with an example
Clustering Analysis using Python with an example
Implementing an Artificial Neural Network
Backpropagation
90 Day Plan to Learn and Implement Machine Learning
Conclusion
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
