Deep Learning with Python

Our classrooms are filled with curious, innovative minds that our current instructional practices aren’t embracing. When educators provide explicit instruction, guidance, and feedback to students and

This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning technique

① Do you know what AI is doing to improve our health and wellbeing?② Does this new technology concern you, or impress you?③ Do you want to know more about the future of AI in healthcare?Technology continues to advance at a pace that can seem bewildering. Nowhere else is it moving faster than in the health sector, where ♥AI is now being used to improve millions of lives♥.In this book, ◆ Artificial Intelligence in Healthcare: AI, Machine Learning, and Deep and Intelligent Medicine Simplified for Everyone ◆, you can discover the great improvements that AI is making, with chapters covering: ✓ The current applications and future of AI in healthcare and all major medical specialties✓ The benefits and risks weighed up✓ The ethics involved✓ Machine learning and data science simplified✓ AI's role in medical research and education, health insurance, drug discovery, electronic health records, and the fight against COVID-19✓ The roles that major corporations and start-up companies are playing✓ The

Modern NLP techniques based on machine learning radically improve the ability of software to recognize patterns, use context to infer meaning, and accurately discern intent from poorly-structured text

What better way is there to learn a programming language than with a game-oriented approach? If you ask the many readers that have made this book's prequel, PYTHON PROGRAMMING FOR THE ABSOLUTE BEGINNE

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

Discover the Most Comprehensible Beginner's Guide to Coding for Children, Packed with Fun Coding Activities and Games All Kids Will LoveDear friend, Do you have a little smartypants running around your home? Would you like to ensure the brightest possible future for your child? If so, then this book is a perfect choice for both of you.This bundle is an excellent choice for all children who are interested in the world of computers, programming, and coding. It is specially made for kids aged from 8 to 12 that have no prior knowledge of coding.Here is what this bundle can teach your child: Game-based learning - there's no better way for kids to learn than through playing and fun activities that will capture your child's attention.40+ fun coding activities and games - this bundle is packed with more than 40 fun activities that will introduce coding to your child and help them grasp the basic skills from a very young age.Easy-to-follow guidance - Straightforward directions and tips keep you

用 Python + Keras 實踐深度學習, 解開神經網路模型的黑盒子在高階函式庫 Keras 的幫助下, 用 6 行程式就可寫一隻深度學習神經網路的程式, 建構深度學習模型就像玩樂高積木一樣, 可以輕易將各種神經網路組合在一起, 而每一種模型可用來解決不同的問題。正宗 Keras 大神著作，正體中文版重磅登場本書為 Keras 之父 François Chollet 親自撰寫, 詳細解說神經

For beginners and experienced programmers, this guide to Python provides practical instruction for developing useful applications with this popular multi-platform open source language. Beginning with

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options f

本書共22章，分為三個部分。第一部分(第1～5章)為Python及應用數學基礎部分，介紹Python和TensorFlow的基石Numpy，深度學習框架的鼻祖Theano，以及機器學習、深度學習算法應用數學基礎等內容。第二部分(第6～20章)為深度學習理論與應用部分，介紹機器學習的經典理論和算法，深度學習理論及方法，TensorFlow基於CPU、GPU版本的安裝及使用、TensorFlow基礎、

Learning Python just got fun for kids!Learning to code is just like playing a new sport or practicing an instrument—just get started! From the basic building blocks of programming to creating your ver

What makes a good relationship? How does flight influence behavior for humans and birds? Is it ever permissible to lie? Reframing our units and lessons with questions such as these makes learning mor

Anew title in The QuestKids children's series thatwas launched by In Easy Steps in 2018, designed to make learning fun forchildren.Coding with Python- Create Amazing Graphics introducescoding in Python through a variety of projects. Each one teaches new codingconcepts and results in some amazing graphics.Discover how to mix colours, make patterns, draw 2D and 3Dshapes.Learn how to use loops, variables, random numbers, andfunctions in Python. Packed with challenges, tips, and extensions to keep allbudding coders engaged and eager to keep learning and creating!To create the games in this book, children will need a desktopcomputer or a laptop. The games require a proper keyboard so will not work wellon a tablet or iPad. It is recommended that children should be supervised whenusing the internet, especially when using a new website. Thisis the UK English edition.

Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python. What You Will LearnUse Python and numerical computation to demonstrate the power of simulationChoose a paradigm to run a simulationDraw statistical insights from numerical experimentsKnow how simulation is used to solve real-world problems Who This Book Is ForEntry-level to mid-level Python developers from various backg

Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and

As an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.While there are many books, websites, and online courses about the topic, we break down Python programming into easily digestible lessons of less than 5 minutes each, following our BiteSize approach. Each lesson begins with a clear and short introduction to the topic. This gives you a strong base to start from and gets you ready for deeper learning. Then, you will see coding demonstrations that show the ideas discussed. These examples are simple and useful, helping you really understand the concepts. You'll then practice tasks at different difficulty levels, so you can test your knowledge and increase your confidence. You'll also play with case studies to solve real-world problems. Tips are included to show how you can incorporate generative AI int

Everything you need to know to get into Python coding, with 7 books in one Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language. Get started coding in Python--even if you're new to computer programmingReference all the essentials and the latest updates, so your code is air-tightLearn how Python can be a solution for large-scale projects and big datasetsAccelerate your career path with this comprehensive guide to learning PythonExperienced and would-be coders alike will love this easy-to-follow guide to learning

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the Worl

Migrate from pandas and scikit-Learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Na鴳e Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using

Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how t

With new jungle friends to meet, colours to name, things to spot and lots to count, this peek-through book is perfect to share with little ones.Toddlers are learning new things all the time, and these

Learn the fundamentals of Cython to extend the legacy of your applicationsAbout This BookLearn how to extend C applications with pure Python codeGet more from Python – you'll not only learn Cython, yo

Create descriptors and see ideas and examples of how to use descriptors effectively. In this short book, you’ll explore descriptors in general, with a deep explanation of what descriptors are, how the

《Python數據挖掘入門與實踐》一書作為數據挖掘入門讀物，介紹了數據挖掘的基礎知識、基本工具和實踐方法，通過循序漸進地講解算法，帶你輕鬆踏上數據挖掘之旅。本書採用理論與實踐相結合的方式，呈現瞭如何使用決策樹和隨機森林算法預測美國職業籃球聯賽比賽結果，如何使用親和性分析方法推薦電影，如何使用樸素貝葉斯算法進行社會媒體挖掘，等等。本書也涉及神經網絡、深度學習、大數據處理等內容。

Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design mod

――――超人氣暢銷書《演算法圖鑑》姊妹作，機器學習初學者最佳入門書！―――― 人工智慧時代關鍵能力！深度學習深在哪裡？強化運算思維，建構邏輯概念，一次弄懂深度學習活用之道！ ★ 精闢剖析深度學習發展史，詳述機器學習的基礎知識！★ 完整解說熱門程式語言第一名Python的環境建構和基本語法！★ 圖像化示範TensorFlow和Keras的安裝，開發AI必學必讀！★ 介紹類神經網路

深度學習（Deep Learning）如今已成為非常活躍的研究領域，同時也為現代機器學習鋪展了一條康莊大道。本書提供許多範例與清楚的說明，引導讀者進一步了解這個複雜領域中的一些主要概念。包括Google、微軟和Facebook這樣的業界龍頭，全都在其內部積極發展深度學習團隊。不過對於一般人來說，深度學習仍舊是個相當複雜而困難的主題。如果您熟悉Python，並具備微積分的背景知識，加上對於機器學習的

If you're a Python, JavaScript, or C# developer and want to learn the basics of object-oriented programming with real-world examples, then this book is for you.

A parent with ASD can provide his or her children with deep love and devoted support, along with a perspective on the world that is wonderfully unique. At the same time, the emotional and physical dem

深度學習正日益深刻地滲入我們的生活，從建議內容到在任務關鍵型和安全關鍵型應用中發揮核心作用，其影響無所不在。然而，隨著這些算法影響力的逐漸擴大，人們對於依賴這些算法的系統安全性和魯棒性的擔憂也日益加劇。簡言之，傳統的深度學習方法往往難以察覺自身的知識邊界，即它們“不知其所不知”。貝葉斯深度學習(Bayesian Deep Learning，BDL)領域包含一系列利用深度網絡進行近似貝葉斯推理的方法。這些方法通過揭示模型對其預測結果的置信度，增強了深度學習系統的魯棒性，使我們能夠更謹慎地將模型預測融入實際應用中。《Python貝葉斯深度學習》將引領你踏入迅速發展的不確定性感知深度學習領域，助你深入理解不確定性估計在構建魯棒性的機器學習系統中的重要價值。你將學習多種流行的BDL方法，並通過涵蓋多種應用場景的Python實用示例來掌握這些方法的實現技巧。讀完本書後，你將深刻理解BDL及其優勢，並能夠為更安全、更魯棒的深度學習系統開發貝葉斯深度學習模型。主要內容：● 了解貝葉斯推理和深度學習的優缺點● 了解貝葉斯神經網絡(Bayesian Neural Network，BNN)的基本原理● 了解主要貝葉斯神經網絡實現/近似之間的差異● 了解生產環境中概率深度神經網絡的優勢● 在Python代碼中實現各種貝葉斯深度學習方法● 運用貝葉斯深度學習方法解決實際問題● 學習如何評估貝葉斯深度學習方法並為特定任務選擇最佳方法● 在實際深度學習應用中處理“分布外”數據

Machine learning-a computer's ability to learn-is transforming our world: it is used to understand images, process text, make predictions by analyzing large amounts of data, and much more. It can be used in nearly every industry to improve efficiency and help stakeholders make better decisions. Whatever your industry or hobby, chances are that these modern artificial intelligence methods will be useful to you as well.Introduction to Machine Learning weaves reproducible coding examples into explanatory text to show what machine learning is, how it can be applied, and how it works. Perfect for anyone new to the world of AI or those looking to further their understanding, the text begins with a brief introduction to the Wolfram Language, the programming language used for the examples throughout the book. From there, readers are introduced to key concepts before exploring common methods and paradigms such as classification, regression, clustering, and deep learning. The math content is kep