Deep Learning with Python

In many societies, histories of exclusion, racism and nationalist violence often create divisions so deep that finding a way to deal with the atrocities of the past seems nearly impossible. These societies face difficult practical questions about how to devise new state and civil society institutions that will respond to massive or systematic violations of human rights, recognize victims and prevent the recurrence of abuse. Identities in Transition: Challenges for Transitional Justice in Divided Societies brings together a rich group of international researchers and practitioners who, for the first time, examine transitional justice through an 'identity' lens. They tackle ways that transitional justice can act as a means of political learning across communities; foster citizenship, trust and recognition; and break down harmful myths and stereotypes, as steps toward meeting the difficult challenges for transitional justice in divided societies.

"This is a wonderful book with deep insight into the relationship between teachers' action and result of student learning. It discusses from different angles impact of action research on student lear

"This is a wonderful book with deep insight into the relationship between teachers' action and result of student learning. It discusses from different angles impact of action research on student lear

How can the world's religious traditions debate within the public sphere? In this book, Nicholas Adams shows the importance of Habermas' approaches to this question. The full range of Habermas' work is considered, with detailed commentary on the more difficult texts. Adams energetically rebuts some of Habermas' arguments, particularly those which postulate the irrationality or stability of religious thought. Members of different religious traditions need to understand their own ethical positions as part of a process of development involving ongoing disagreements, rather than a stable unchanging morality. Public debate additionally requires learning each other's patterns of disagreement. Adams argues that rather than suspending their deep reasoning to facilitate debate, as Habermas suggests, religious traditions must make their reasoning public, and that 'scriptural reasoning' is a possible model for this. Habermas overestimates the stability of religious traditions. This book offers a

How can the world's religious traditions debate within the public sphere? In this book, Nicholas Adams shows the importance of Habermas' approaches to this question. The full range of Habermas' work is considered, with detailed commentary on the more difficult texts. Adams energetically rebuts some of Habermas' arguments, particularly those which postulate the irrationality or stability of religious thought. Members of different religious traditions need to understand their own ethical positions as part of a process of development involving ongoing disagreements, rather than a stable unchanging morality. Public debate additionally requires learning each other's patterns of disagreement. Adams argues that rather than suspending their deep reasoning to facilitate debate, as Habermas suggests, religious traditions must make their reasoning public, and that 'scriptural reasoning' is a possible model for this. Habermas overestimates the stability of religious traditions. This book offers a

Ways with Words, first published in 1983, is a classic study of children learning to use language at home and at school in two communities only a few miles apart in the south-eastern United States. 'Roadville' is a white working-class community of families steeped for generations in the life of textile mills; 'Trackton' is an African-American working-class community whose older generations grew up farming the land, but whose existent members work in the mills. In tracing the children's language development the author shows the deep cultural differences between the two communities, whose ways with words differ as strikingly from each other as either does from the pattern of the townspeople, the 'mainstream' blacks and whites who hold power in the schools and workplaces of the region. Employing the combined skills of ethnographer, social historian, and teacher, the author raises fundamental questions about the nature of language development, the effects of literacy on oral language habit

Far, far away, in deep, dark space, was a star. A tiny twinkle. But it was Star Boy's home. Star Boy lived there all alone, with only his robot, Ace, for company. And although Ace was fun to play with

Two touching, ghostly tales by Harriet Goodwin and Leon Rosselson. In the first, Joe, struggling to come to terms with his mother's death, finds himself drawn into a spooky legend that lies deep benea

Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. It examines both the commonly used traffic analysis methodologies as well the emerging ones that use deep learning methods. The book also shows how to understand statistical models and machine learning algorithms, and how to apply them to traffic modelling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning is for researchers and practitioners who want to improve the performance of intelligent transportation systems.

Introducing Your Guide to Learning PythonIllustrated Guide to Learning Python is designed to bring developers and others who are anxious to learn Python up to speed quickly. Not only does it teach the

Are You Interested In Learning Python? Would You Like To Know The Secrets To Programing? Want To Master The Basics Of Python Programming? Yes, this is the perfect book for you to get started with thi

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

Become a Python Programming Expert With Ease!What if you had access to a python guide that literally takes you step by step through every essential process of learning the python language? Imagine you

If you are a Python programmer who wants to get started with performing data analysis using pandas and Python, this is the book for you. Some experience with statistical analysis would be helpful but

本書以自上而下和自下而上的方法來展示針對不同領域實際問題的深度學習解決方案，包括圖像識別、自然語言處理、時間序列預測和機器人操縱等。還討論了採用諸如TensorFlow、PyTorch、Keras和CNTK等流行的深度學習開源框架用於實際問題的解決方案及其優缺點。本書內容包括：用於深度學習的編程環境、GPU計算和雲端解決方案；前饋神經網絡與卷積神經網絡；循環與遞歸神經網絡；強化學習與生成對抗網絡；

【我們正在親手毀掉下一代的腦袋嗎？】Amazon 教育類冠軍書、哈佛神經科學家最沉痛的警告。為什麼給孩子最好的平板、最新的 AI 軟體，他們的學力與專注力卻持續崩盤？我們被告知「科技即進步」，但數據顯示：這是一場巨大的數位錯覺。哈佛神經科學家 Jared Cooney Horvath 博士，透過數十年的腦科學研究，揭穿 EdTech（教育科技）的神話：❌ 多媒體教學不等於學習：大腦在螢幕前更傾向於「快速瀏覽」，而非「深度思考」。❌ 數位工具的「培訓輪」效應：軟體讓孩子看起來學得很快，但一旦拿掉科技，他們連基本的邏輯與記憶都無法建立。❌ AI 的陷阱：一個不需要思考就能得到答案的環境，正在弱化人類大腦最核心的競爭力。這不是一本反對科技的書，而是一本「支持學習」的戰鬥手冊！Horvath 博士將告訴你，如何透過「人類的連結」重建教室的溫度，並為你的孩子打造一個足以應對 AI 時代的強健大腦。➤如果您是家長：請翻開這本書，了解如何守護孩子的注意力。➤如果您是老師：這本書將告訴您，為什麼您比任何軟體都更無可取代。別讓數位科技，成為孩子思維退化的推手。《The Digital Delusion》——現在就奪回教育的自主權！Our children are struggling.Schools, once alive with deep learning born of human connection, are now dominated by screens. The result is unmistakable: falling performance, fractured attention, and the slow erosion of rigorous thought.We were told that classroom technology was progress. It wasn't. In THE DIGITAL DELUSION, neuroscientist and educator Dr. Jared Cooney Horvath reveals why digital tools in school consistently undermine learning -- and what parents, teachers, and schools

A hands-on, code-based guide to leveraging Julia in a variety of scientific and data-driven scenarios Key Features: Augment your basic computing skills with an in-depth introduction to JuliaFocus on topic-based approaches to scientific problems and visualisationBuild on prior knowledge of programming languages such as Python, R, or C/C++Purchase of the print or Kindle book includes a free PDF eBook Book Description: Julia is a well-constructed programming language which was designed for fast execution speed by using just-in-time LLVM compilation techniques, thus eliminating the classic problem of performing analysis in one language and translating it for performance in a second.This book is a primer on Julia's approach to a wide variety of topics such as scientific computing, statistics, machine learning, simulation, graphics, and distributed computing.Starting off with a refresher on installing and running Julia on different platforms, you'll quickly get to grips with the core concept

This book provides a comprehensive foundation of machine learning. To answer the questions of what to learn, how to learn, what to get from learning, and how to evaluate, as well as what is meant by learning, the book focuses on the fundamental basics of machine learning, its methodology, theory, algorithms, and evaluations, together with some philosophical thinking on comparison between machine learning and human learning for machinery intelligence.The book is organized as follows: Introduction (Chapter 1), Evaluation (Chapter 2), Supervised learning (Chapters 3, 4, and 5), Unsupervised learning (Chapter 6), Representation learning (Chapter 7), Problem decomposition (Chapter 8), Ensemble learning (Chapter 9), Deep learning (Chapter 10), Application (Chapter 11), and Challenges (Chapter 12).The book can be used as a textbook for college, undergraduate, graduate and PhD students majored in computer science, automation, electronic engineering, communication, ect. It can also be used as

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

Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you'll get familiarized with tensors, a type of data structure u

Learning that her husband has landed in grave danger while deep undercover on a secret assignment, Molly Murphy Sullivan embarks on a dangerous cross-country journey with her young son while contempla