Python machine learning

《Python+Office：輕松實現Python辦公自動化》分為6篇。第1篇Python編程基礎篇，介紹Python語言及開發環境搭建、Python編程基礎、利用Python進行數據準備；第2篇Excel數據自動化處理篇，介紹利用Python進行數據處理、數據分析和數據可視化；第3篇Word文本自動化處理篇，介紹文本自動化處理、利用Python進行文本自動化處理、利用Python制作企業運營月報Word版；第4篇幻燈片自動化制作篇，介紹幻燈片自動化制作、利用Python進行幻燈片自動化制作、利用Python制作企業運營月報幻燈片；第5篇郵件自動化處理篇，介紹利用Python批量發送電子郵件、利用Python獲取電子郵件、利用Python自動發送電商會員郵件；第6篇文件自動化處理篇，介紹利用Python進行文件自動化處理。《Python+Office：輕松實現Python辦公自動化》從實際工作需求的角度，詳細介紹了基於Python的辦公自動化技術，既可以作為職場人員學習Python辦公自動化的自學用書，也可以作為高等院校相關專業學生的參考用書。

《Python超實用：全彩：你的Python實踐工具書》全面介紹了Python與編程的基礎知識，也講解了如何開發應用於不同場景的程序。讀者可跟隨作者的講解進行實際的操作和練習。《Python超實用：全彩：你的Python實踐工具書》是面向各層次的Python讀者而作的Python入門書，全書共分為9個部分，主要介紹了包括Python的基本概念、Python庫、Tello EDU編程、用Python

Originally published in 1992, this title reviews seven major subareas in artificial intelligence at that time: knowledge acquisition; logic programming and representation; machine learning; natural la

Explore the technology that is changing our world!Imagine a machine that can learn from experience and teach itself new things - that's AI in action! Trace the development of intelligent machines fr

《Python編程實戰》是一本語法與實踐相結合的Python入門教程，以簡明的語言、易懂的案例介紹Python編程。 《Python編程實戰》共11章，其中，第1-4章介紹Python的基礎知識，如Python的下載與安裝，Python結構，Python程序、算法和函數，Python擴展、文件和繪圖；第5-8章介紹Python的類和方法、標準庫、高級編程和仿真測試

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

WINNER OF THE ROYAL SOCIETY INSIGHT INVESTMENT SCIENCE BOOK PRIZE 2020How proteins, machine learning and molecular chemistry can teach us about the complexities of human behaviour and the world around

The human body is a wonderful biological machine. Explore it page by page, learning all about organs and bones, as well as the different stages of life. Marvel at the breathtaking beauty of biology, w

Machine learning, big data and AI are reshaping the human experience and forcing us to develop a new ethical intelligence. Peter Hershock offers a new way to think about attention, personal presence,

Machine learning, big data and AI are reshaping the human experience and forcing us to develop a new ethical intelligence. Peter Hershock offers a new way to think about attention, personal presence,

In the age of data-driven problem-solving, applying sophisticated computational tools for explaining substantive phenomena is a valuable skill. Yet, application of methods assumes an understanding of the data, structure, and patterns that influence the broader research program. This Element offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered in this Element, in addition to R code and real data to facilitate interaction with the concepts. Upon setting the stage for clustering, the following algorithms are detailed: agglomerative hierarchical clustering, k-means clustering, Gaussian mixture models, and at a higher-level, fuzzy C-means clustering, DBSCAN, and partitioning around medoids (k-medoids) clustering.

Based on interdisciplinary research into 'Directional Change', a new data-driven approach to financial data analysis, this book applies machine learning to financial market monitoring and algorithmic

It will soon be impossible to tell what is real and what is fake. Recent advances in AI mean that by scanning images of a person (for example using Facebook), a powerful machine learning system can

Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to “learn” complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specific

Surrogates: a graduate textbook, or professional handbook, on topics at the interface between machine learning, spatial statistics, computer simulation, meta-modeling (i.e., emulation), design of expe

Both a serious academic text and an intriguing story, this seventh edition reflects a significant update in research, theory, and applications in all areas. It presents a comprehensive view of the historical development of learning theories from behaviorist through to cognitive models. The chapters also cover memory, motivation, social learning, machine learning, and artificial intelligence. The author's highly entertaining style clarifies concepts, emphasizes practical applications, and presents a thought-provoking, narrator-based commentary. The stage is given to Mrs Gribbin and her swashbuckling cat, who both lighten things up and supply much-needed detail. These two help to explore the importance of technology for simulating human cognitive processes and engage with current models of memory. They investigate developments in, and applications of, brain-based research and plunge into models in motivation theory, to name but a few of the adventures they embark upon in this textbook.

Both a serious academic text and an intriguing story, this seventh edition reflects a significant update in research, theory, and applications in all areas. It presents a comprehensive view of the historical development of learning theories from behaviorist through to cognitive models. The chapters also cover memory, motivation, social learning, machine learning, and artificial intelligence. The author's highly entertaining style clarifies concepts, emphasizes practical applications, and presents a thought-provoking, narrator-based commentary. The stage is given to Mrs Gribbin and her swashbuckling cat, who both lighten things up and supply much-needed detail. These two help to explore the importance of technology for simulating human cognitive processes and engage with current models of memory. They investigate developments in, and applications of, brain-based research and plunge into models in motivation theory, to name but a few of the adventures they embark upon in this textbook.

全書以“計算思維”培養為目標，貫穿理解和運用計算生態的 Python 語言教學思想，系統展示了 Python 語言學習路徑。本書分為 12 章，主要內容如下：第 1 章講解 Python 基礎知識與概念，以及 Python 的交互式解釋器 IDLE；第 2 章講解 Python 語言語法基礎；第 3 章講解Python 控制語句；第 4 章講解 Python 數據結構；第 5 章講解 Python

Quilters want to finish their quilts--and that means doing their own machine quilting. In Free-Motion Quilting 101, teacher and quilter Ashley Nickels provides in-depth instruction on learning the tec

“[Coleman] argues that the algorithms of machine learning — if they are instilled with human ethics and values — could bring about a new era of enlightenment.” —San Francisco ChronicleThe Age of Intel

Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and you

The field of artificial intelligence (AI) has grown dramatically in recent decades from niche expert systems to the current myriad of deep machine learning applications that include personal assistant

For courses in machine shop, machine tool technology, machining processes/manufacturing processes technology, industrial technology, industrial mechanics, and industrial engineering at the undergradua

《Python程序設計》由淺入深、循序漸進地通過大量實例闡述了Python語言的基礎知識，同時介紹如何使用Python來解決科學計算問題，以及如何使用Python面向對象編程，還介紹了很多Python的應用技術。《Python程序設計》共9章，第1章主要是Python語言概述，第2章介紹Python的基本元素，第3章介紹Python語言的流程控制和循環語句，第4章介紹Python函數的定義與使用，

If you’re a developer familiar with AI, machine learning, and computer vision, this practical book provides you with a foundational understanding of augmented and virtual reality functions. AR a

Second edition of the best selling Python book in the world. A fast-paced, no-nonsense guide to programming in Python. This book teaches beginners the basics of programming in Python with a focus on r

本書通過大量實例，全面、系統、深入地講解了Python編程基礎及應用開發。主要包括： Python概述及開發環境、Python編程基礎、Python函數及模塊、面向對象編程、 Python界面設計、Python數據庫編程、Python網絡編程、Python網站開發、Python繪圖與圖像處理、Python科學計算。

The award-winning author of The Music of the Primes explores the future of creativity and how machine learning will disrupt, enrich, and transform our understanding of what it means to be human.Can a well-programmed machine do anything a human can—only better? Complex algorithms are buying our groceries, picking our partners, and driving our investments. They can navigate more data than a doctor or lawyer and act with greater precision. For many years we’ve taken solace in the notion that they can’t create. But now that algorithms can learn and adapt, does the future of creativity belong to machines too?It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. Programs like Deep Dream produce d

Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight in

Digitization is reshaping our careers, companies, and industries. Machine learning, artificial intelligence, and robotics are surpassing human capabilities across broad sectors of the economy but also

Brain-machine interfacing or brain-computer interfacing (BMI/BCI) is an emerging and challenging technology used in engineering and neuroscience. The ultimate goal is to provide a pathway from the bra

Artificial intelligence and related technologies are changing both the law and the legal profession. In particular, technological advances in fields ranging from machine learning to more advanced robo

This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensivel

Create applications using Industry 4.0. Discover how artificial intelligence (AI) and machine learning (ML) capabilities can be enhanced using the Internet of things (IoT) and secured using Blockchain

This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and

In spite of intense but traditional academic effort, a unique formal framework to study civil conflict has been elusive. This book uses predictive machine learning to highlight a framework to identify

This book shows machine learning enthusiasts and practitioners how to get the best of both worlds by deriving Fisher kernels from deep learning models. In addition, the book shares insight on how to s

Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization.Security has become a "big data" problem. The growth rate of malw

This book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireles