Deep Learning with Python

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.

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

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

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

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

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

【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

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

Child's Play continues its reputation for high quality, 3D engineering with another innovative approach to play and learning. Discover the deep ocean jungle as you unravel this fascinating pop-up book