Python machine learning

Available in paperback! A young chapter book series starter about a chicken who loves math, science, and learning new things--by New York Times bestselling author Nancy Krulik. Perfect for fans of Unlimited Squirrels and Bumble and Bee. Chirpy is a young chicken stuck in the family coop. But she's not like the other chickens who just sit around peck peck pecking all day. She's intrigued by the children who come home from a place called school. They always look so happy! (Well, most days.) So Chirpy sneaks onto the bus one morning, hides in the classroom . . . and discovers a true love of math. When she shares what she's learned with the other chickens, they think she's one kernel short of a cob. Even so, Chirpy is determined to find a formula for fowl success by pecking away. But when a hungry fox tries to attack the coop, can she find the equation for a simple solution? With lively two-color art throughout, plus a fun hands-on simple machine activity, this eggs-ellent young chapter bo

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding bot

Harley Hitch returns for an airborne adventure in this highly illustrated fiction series about a determined young inventor from award-winning author Vashti Hardy. The Aviation Parade is coming to Forgetown this summer, and Harley has her sights set on creating a flying machine that will really stand out: a robot hippogriff! And if the creature impresses Cosmo's mum enough, surely Cosmo will be able to keep it as a pet? But Harley wants the flying machine to be a surprise for everyone. She soon finds that keeping secrets leads to tricky explanations and lots of trouble - especially when REAL hippogriffs arrive and cause chaos! Join Harley, her robot dog Sprocket and best friend Cosmo for problem-solving adventures and mysteries in a world where science rules and technology grows in the forest! A rollicking adventure that celebrates STEM learning! Highly illustrated with lively, humourous illustrations by George Ermos.Vashti Hardy is an award-winning author of children's books. Her novel

人工智慧（AI）將改變人類與所有產業的生態。 如果你對人工智慧，沒有全面的了解，那就跟不上時代了。很多影響人類的科技發展，都無法做出正確的判斷。 一個知名的投資專家說，比起5G，人人手上有，處處可見基地台，AI只有少數大公司用得上，到底有無潛力？有！但是不要想得太美了。 他說的對不對？很難判斷嗎？讀完本書，你就會找到正確的解答。 其實AI有三種，一種是雲端，就是連到那幾家大公司的機房，用他們大的嚇死人的算力。 一種是在本地運算，如汽車的自動駕駛。第三種則是運用在最前端的偵測裝置，以求最快的反應時間。 所以你說AI只有幾家大公司用得上，好像也沒有那麼對。 所以你要把它想得美一點，它是平地一聲雷，輝達、台積電的股價都應該後面加一千個零，是嗎？ 但是你知道有資訊科技以來，人類至少經過三次AI的浪潮。很多公司運用AI運用得嚇嚇叫，如文藝復興基金，用機器學習投資，20年來平均的年化報酬率遠勝巴菲特。 所以你說AI前程遠大！很OK，但它說他橫空出世？倒也未必，它只是一個連續的改善過程！ 當然有關AI最誇張的是想像是《魔鬼終結者》，一個是幹掉想毁滅人類的傢伙，而且他可以和人腦一樣的運作。不過有的人是殺人魔，有的人是慈善家。不知可以和人腦一樣運作的AI是慈善家或是殺人魔？ AI的形式有很多種，從撰寫大量複雜的函式來實現人工智慧的專家系統，到以大量資料反求智慧判定函式的演算法，如支援向量機（Support Vector Machine, SVM）、決策樹（Decision Tree）等，此領域統稱為機器學習（Machine Learning, ML），而運用神經網路技術，將網路的節點深度擴展延伸，以獲得更好的智慧判定效果，則稱為深度學習（Deep Learning, DL）。 你越了解AI的技術背景，就越能掌握它未來對人類的影響。如果你想投資AI相關產業，就更是需要深入了解了。 任何資訊科技的運用都有兩個層面，軟體以及執行軟體的硬體。本書除了說明AI運用的基本原理之外，也將詳細說明有關AI的軟體及硬體產業鏈。對一個投資人而言，完整的了解一個產業的上下游關係，是十分必要的。 總不能輝達業績創新高，而你完全沒有概念台積電會好還是不好吧？ 本書以圖文對照的方式，讓你對AI有清楚的認識。不論投資、或生活，可以在新科技浪潮中，穩定前行。 本書特色 ◎100個單元，

Discover two sides of history with the Time Travel Twins!Twins, Scarlett and Thomas, are learning about the Romans at school. So Grandad uses his time machine to send them back to Roman Britain.Scarlett finds herself in a Roman camp and is chosen as a slave by the Emperor Claudius’s daughter, Antonia. The two become friends and Scarlett sees first hand the glamour and treachery of the Roman court.Thomas joins a rabble of local kids who hate the Romans. Their leader is a small red-headed girl called Boudicca. Even when the kids are overwhelmed and taken as slaves, Bou hatches another plan to attack the Romans.Will the twins find each other and escape, or will they both be stuck as Roman slaves for ever?

這是一本介紹如何應用大數據和機器學習技術來解決投資問題並提高投資績效的專著。近年來，機器學習和數據科學在投資中發揮著越來越大的作用。從本質上講，機器學習模型在挖掘數據背後的非線性關係上要強于傳統模型。借助機器學習和大數據，投資經理能夠做出以往傳統模型無法實現的預測，進而做出明智的決策。然而，在投資中，並不是所有的數據集和機器學習技術都對金融應用有用，也不是所有的機器學習技術都可以“即插即用”。《大數據、機器學習與量化投資》這本書由資深量化分析專家托尼‧吉達主編，彙集了多位業內頗具影響力的專家學者的前沿分享，闡釋如何應用大數據和機器學習技術來解決投資問題並提高投資績效。這本書共有13章，理論嚴謹，案例豐富，內容涵蓋機器學習在投資管理中的應用現狀和前景、另類數據和大數據在宏觀交易中的應用、處理大數據集的難點和解決方案、挖掘社交媒體數據集分析企業文化、使用自然語言處理技術進行投資者情緒分析、基於支持向量回歸的全球戰術性資產配置策略、強化學習和深度學習在投資組合優化中的應用等主題，可以作為量化投資從業者、金融算法研究人員、高等院校計算機專業和金融工程專業的師生以及機器學習愛好者的參考用書。

機器學習(Machine Learning，ML)是人工智能的一個分支，它是一門多領域交叉學科，專門研究計算機怎樣模擬或實現人類的學習行為，涉及概率論、統計學、逼近論、凸分析、算法複雜度理論等多門學科。機器學習方法可以根據經驗數據自動完成模型參數學習，而不需要人為設定規則，大幅降低了人工分析的工作量和難度，已成為目前解決人工智能相關問題的主要方式。

The book elucidates the revolutionary and riveting research in the ultramodern domain of drone technologies, drone-enabled IoT applications, and artificial intelligence-based smart surveillance. The book explains the most recent developments in the field, challenges, and future scope of drone technologies. Beyond that, it discusses the importance of a wide range of design applications, drone/UAV development, and drone-enabled smart healthcare systems for smart cities. It describes pioneering work on mitigating cyber security threats by employing intelligent machine learning models in the designing of IoT-aided drones. The book also has a fascinating chapter on application intrusion detection by drones using recurrent neural networks. Other chapters address interdisciplinary fields like artificial intelligence, deep learning, the role of drones in healthcare in smart cities, and the importance of drone technology in agriculture.

Finance students and practitioners may ask: can machines learn everything? Could AI help me? Computing students or practitioners may ask: which of my skills could contribute to finance? Where in finance should I pay attention? This book aims to answer these questions. No prior knowledge is expected in AI or finance.Including original research, the book explains the impact of ignoring computation in classical economics; examines the relationship between computing and finance and points out potential misunderstandings between economists and computer scientists; and introduces Directional Change and explains how this can be used.To finance students and practitioners, this book will explain the promise of AI, as well as its limitations. It will cover knowledge representation, modelling, simulation and machine learning, explaining the principles of how they work. To computing students and practitioners, this book will introduce the financial applications in which AI has made an impact. This

This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches.The book's authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents

★☆★ AI 影像辨識一本精通！ ★☆★ ★☆★ 超過 200 個完整範例程式碼 ★☆★ AI 影像辨識是近年來非常夯的議題，隨著資訊科技的蓬勃發展，越來越多好用的工具推陳出新，也越來越容易跨入 AI 影像辨識領域，不論是電子、資訊領域、醫療、百貨，各行各業中陸續都能看到 AI 影像辨識的應用。 Python 是目前入門 AI 影像辨識最快速的程式語言，透過 Python 的 OpenCV 函式庫，並搭配其他方便的函式庫，就能輕鬆入門 AI 影像辨識，OpenCV 除了能針對影像進行全面的處理，也是大多數 AI 影像辨識的敲門磚，常應用於擴增實境、臉部辨識、手勢辨識、動作辨識、運動跟蹤、物體辨識或圖像分割...等領域。 本書會從 OpenCV 出發，從 OpenCV 最基本的存取圖片影片，影像色彩、影像剪裁、影像變形、加入文字、繪圖、影像效果進階處理都有完整介紹，並會介紹 OpenCV 內建的影像辨識方法、Google MediaPipe 的影像辨識方法和 Teachable Machine 影像辨識方法進行 AI 影像辨識，作出許多有趣又實用的影像辨識相關應用。 【精彩收錄】 ▶ OpenCV 深入介紹 ▶ OpenCV 影像色彩調整和轉換 ▶ OpenCV 影像剪裁、變形、加入文字和繪圖 ▶ OpenCV 影像效果進階處理 ▶ OpenCV 偵測滑鼠和鍵盤 ▶ OpenCV 人臉、物件、顏色等影像辨識 ▶ MediaPipe 人臉、姿勢、手勢等影像辨識 ▶ Teachable Machine 人臉、戴口罩等影像辨識 ▶ 辨識手寫數字、年齡、情緒

Cybersecurity attacks grow more complex every day. The first edition of Wilson's COMPTIA PENTEST+ GUIDE TO PENETRATION TESTING helps you gain the knowledge and skills necessary to analyze systems in the same way hackers do. It provides the information you need to successfully pass the CompTIA PenTest+ PTO-002 certification exam and contains detailed examples, projects, and hands-on activities (including virtual machine labs and interactive online features) where you can practice using the actual tools and methodologies needed to be a successful penetration tester. The author begins by exploring the concept of penetration testing, and then walks you through the process of building your own penetration testing lab of virtual machines (hosted on your own computer, which is used to practice the use of pen testing tools and methods). A final project guides you in the creation of a penetration testing report that includes all the areas covered in earlier modules.

Develop the analytical skills that are in high demand in businesses today with Camm/Cochran/Fry/Ohlmann's best-selling BUSINESS ANALYTICS, 5E. You master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills. Real examples and memorable visuals clearly illustrate data and results. Step-by-step instructions guide you through using Excel, Tableau, R or the Python-based Orange data mining software to perform advanced analytics. Practical, relevant problems at all levels of difficulty let you apply what you've learned. Updates throughout this edition address topics beyond traditional quantitative concepts, such as data wrangling, data visualization and data mining, which are increasingly important in today's business environment. MindTap and WebAssign online learning platforms are also available with an interactive eBook, algorithmic practice problems and Exploring Analytics visualizations to strengthen your understanding of key concepts.

An empirical study and analysis of heart disease prediction involves using data analysis techniques to identify patterns and risk factors associated with cardiovascular disease. This approach utilizes machine learning algorithms to classify patients based on their likelihood of developing heart disease.The study involves collecting data on risk factors such as age, gender, family history, blood pressure, cholesterol levels, smoking, and diabetes. Feature selection techniques are used to identify the most important risk factors, and a classification model is trained using these factors. The accuracy of the model is evaluated using metrics such as sensitivity, specificity, and AUC.This empirical study and analysis has several advantages, including the ability to identify new risk factors associated with heart disease, improved accuracy in predicting cardiovascular risk, and the potential to develop more personalized prevention and treatment strategies. This approach has the potential to

With the advent of the Al era, professionals need to select the right tools to meet new opportunities and challenges! This instructional material focuses on the application of big data analysis, text mining, and machine learning in auditing to assist readers in understanding the latest developments in data analysis and smart audit.JCAATs is a new generation audit software developed by Python, which can be executed in a Windows and MAC operation systems with a multi-language, visual, and easy-to-use interface. Non-IT professionals can easily conduct smart data analysis. Through JCAATs' built-in data fusion technology and OPEN DATA connector, heterogeneous data can be quickly analyzed in real-time and effectively identifying anomalies. The features of this book include:The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions. The official textbook endorsed by ICAEA

Over the last half century, "smartness"―the drive for ubiquitous computing―has become a mandate: a new mode of managing and governing politics, economics, and the environment.Smart phones. Smart cars. Smart homes. Smart cities. The imperative to make our world ever smarter in the face of increasingly complex challenges raises several questions: What is this "smartness mandate?" How has it emerged, and what does it say about our evolving way of understanding―and managing―reality? How have we come to see the planet and its denizens first and foremost as data-collecting instruments? In The Smartness Mandate, Orit Halpern and Robert Mitchell radically suggest that "smartness" is not primarily a technology, but rather an epistemology. Through this lens, they offer a critical exploration of the practices, technologies, and subjects that such an understanding relies upon―above all, artificial intelligence and machine learning. The authors approach these not simply as techniques for solving pr

The entanglements of people and data, code and space, knowledge and power: how data and algorithms shape the world―and shape us within that world.With the emergence of a post-truth world, we have witnessed the dissolution of the common ground on which truth claims were negotiated, individual agency enacted, and public spheres shaped. What happens when, as Nietzsche claimed, there are no facts, but only interpretations? In this book, Mark Shepard examines the entanglements of people and data, code and space, knowledge and power that have produced an uncommon ground―a disaggregated public sphere where the extraction of behavioral data and their subsequent processing and sale have led to the emergence of micropublics of ever-finer granularity. Shepard explores how these new post-truth territories are propagated through machine learning systems and social networks, which shape the public and private spaces of everyday life. He traces the balkanization and proliferation of online news and t