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{
"1": {
"title": "Serverless Web Applications with React and Firebase",
"image": "Assets/Web/Serverless Web Applications with React and Firebase/svr.jpg",
"description": "Build rich and collaborative applications using client-side code with React, Redux, and Firebase About This Book 1)A practical guide covering the full stack for web development with React 16 and Firebase 2)Leverage the power of Firebase Cloud Storage, messaging, functions, OAuth, and database security to develop serverless web applications. 3)Develop high-performance applications without the hassle of setting up complex web infrastructure. ReactJS is a wonderful framework for UI development. Firebase as a backend with React is a great choice as it is easy, powerful, and provides great developer experience. It removes a lot of boilerplate code from your app and allows you to focus on your app to get it out quickly to users. Firebase with React is also a good choice for Most Viable Product (MVP) development. This book provides more practical insights rather than just theoretical concepts and includes basic to advanced examples - from hello world to a real-time seat booking app and Helpdesk application This book will cover the essentials of Firebase and React.js and will take you on a fast-paced journey through building real-time applications with Firebase features such as Cloud Storage, Cloud Function, Hosting and the Realtime Database. We will learn how to secure our application by using Firebase authentication and database security rules. We will leverage the power of Redux to organize data in the front-end, since Redux attempts to make state mutations predictable by imposing certain restrictions on how and when updates can happen. Towards the end of the book you will have improved your React skills by realizing the potential of Firebase to create real-time serverless web applications. Style and approach Practical insights rather than just theoretical concepts while including basic to advanced examples - from hello world to a real-time seat booking app and Helpdesk application. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you. ",
"urlid": "1sYzL0Ehe480E40jPTBwAnA0ANjaSUisD"
},
"2": {
"title": "Learning Web Design - A Beginner's Guide to HTML, CSS, JavaScript, and Web Graphics",
"image": "Assets/Web/Learning Web Design - A Beginner’s Guide to HTML, CSS, JavaScript, and Web Graphics/webdesign.jpg",
"description": "Do you want to build web pages but have no prior experience? This friendly guide is the perfect place to start. You'll begin at square one, learning how the web and web pages work, and then steadily build from there. By the end of the book, you'll have the skills to create a simple site with multicolumn pages that adapt for mobile devices. Each chapter provides exercises to help you learn various techniques and short quizzes to make sure you understand key concepts. This thoroughly revised edition is ideal for students and professionals of all backgrounds and skill levels. It is simple and clear enough for beginners, yet thorough enough to be a useful reference for experienced developers keeping their skills up to date. ",
"urlid": "1gzPAvp-LW-rtSTBrHnvj5sy0KeMp7XBW"
},
"3": {
"title": "Vue.js 2 Web Development Projects Learn Vue.js by building 6 web apps",
"image": "Assets/Web/Vue.js 2 Web Development Projects Learn Vue.js by building 6 web apps/vue.jpg",
"description": "Do you want to make your web application amazingly responsive? Are you unhappy with your app's performance and looking forward to trying out ways to make your app more powerful? Then Vue.js, a framework for building user interfaces, is a great choice, and this book is the ideal way to put it through its paces. This book's project-based approach will get you to build six stunning applications from scratch and gain valuable insights in Vue.js 2.5. You'll start by learning the basics of Vue.js and create your first web app using directives along with rich and attractive user experiences. You will learn about animations and interactivity by creating a browser-based game. Using the available tools and preprocessor, you will learn how to create multi-page apps with plugins. You will create highly efficient and performant functional components for your app. Next, you will create your own online store and optimize it. Finally, you will integrate Vue.js with the real-time Meteor library and create a dashboard showing real-time data. By the end of this book you will have enough skills and will have worked through enough examples of real Vue.js projects to create interactive professional web applications with Vue.js 2.5. ",
"urlid": "1fRnlk0WXwYrtsI8Dxzwa4-CmrQOxuHpf"
},
"4": {
"title": "JavaScript The Definitive Guide Master the World's Most-Used Programming Language",
"image": "Assets/Web/JavaScript The Definitive Guide Master the World's Most-Used Programming Language/js.jpg",
"description": "JavaScript is the programming language of the web and is used by more software developers today than any other programming language. For nearly 25 years this best seller has been the go-to guide for JavaScript programmers. The seventh edition is fully updated to cover the 2020 version of JavaScript, and new chapters cover classes, modules, iterators, generators, Promises, async/await, and metaprogramming. You’ll find illuminating and engaging example code throughout. This book is for programmers who want to learn JavaScript and for web developers who want to take their understanding and mastery to the next level. It begins by explaining the JavaScript language itself, in detail, from the bottom up. It then builds on that foundation to cover the web platform and Node.js. ",
"urlid": "1lnrr8Qazg8HWDEetvzXsYHnGtw1szoaA"
},
"5": {
"title": "Modern Full-Stack Development Using TypeScript, React, Node.js, Webpack, and Docker",
"image": "Assets/Web/Modern Full-Stack Development Using TypeScript, React, Node.js, Webpack, and Docker/full stack.jpg",
"description": "Explore what React, Node, TypeScript, Webpack, and Docker have to offer individually, and how they all fit together in modern app development. React is one of the most popular web development tools available today, and Node.js is extremely popular for server-side development. The fact that both utilize JavaScript is a big selling point, but as developers use the language more, they begin to recognize the shortcomings, and that’s where TypeScript comes in and why it’s gaining in popularity quickly. Add Webpack and Docker to the mix, and you’ve got a potent full development stack on which to build applications. You’ll begin by building a solid foundation of knowledge and quickly expand it by constructing two different real-world apps. These aren’t just simple, contrived examples but real apps that you can choose to install on your servers and use for real. By the end, you will have a solid grasp of building apps with React, Node.js, and TypeScript and a good grasp on how Webpack can be used to optimize and organize your code for deployment. You’ll also understand how Docker can be used to run the apps you build in a clear and well-defined way, all of which will be able to springboard you into creating more advanced apps on your own. What You'll Learn Get a project started and logically structure it Construct a user interface with React and Material-UI Use Web Sockets for real-time communication between client and server Build a REST API with Node and Express as another approach to client-server communication Package the app with Webpack for optimized delivery Take a completed app and wrap it up with Docker for easy distribution Review a host of other ancillary topics including NPM, Semantic versioning, Babel, NoSQL, and more Who This Book Is For Web developers with basic knowledge of HTML, JavaScript, CSS, and CLI tools who are interested in and in all aspects of application development, and using TypeScript instead of straight JavaScript. ",
"urlid": "1MC-vGYDC_Mt-KIxO2vie--gaPOD6KpSx"
},
"6": {
"title": "Practical Node.js Building Real-World Scalable Web Apps",
"image": "Assets/Web/Practical Node.js Building Real-World Scalable Web Apps/pnodejs.jpg",
"description": "Learn how to build a wide range of scalable real-world web applications using a professional development toolkit. If you already know the basics of Node.js, now is the time to discover how to bring it to production level by leveraging its vast ecosystem of packages.With this book, you'll work with a varied collection of standards and frameworks and see how all those pieces fit together. Practical Node.js takes you from installing all the necessary modules to writing full-stack web applications. You'll harness the power of the Express.js and Hapi frameworks, the MongoDB database with Mongoskin and Mongoose. You'll also work with Pug and Handlebars template engines, Stylus and LESS CSS lanaguages, OAuth and Everyauth libraries, and the Socket.IO and Derby libraries, and everything in between. This exciting second edition is fully updated for ES6/ES2015 and also covers how to deploy to Heroku and AWS, daemonize apps, and write REST APIs. You’ll build full-stack real-world Node.js apps from scratch, and also discover how to write your own Node.js modules and publish them on NPM. Fully supported by a continuously updated source code repository on GitHub and with full-color code examples, learn what you can do with Node.js and how far you can take it! Web developers who have some familiarity with the basics of Node.js and want to learn how to use it to build apps in a professional environment. ",
"urlid": "1n7C4TEq3QPvZn9IyrAmkgxYAgHw5fYeP"
},
"7": {
"title": "Machine Learning Using Python",
"image": "Assets/ML & AI/Machine Learning Using Python/MLPy.jpg",
"description": "Are you ready to start your new exciting career? Ready to crush your machine learning career goals? Are you overwhelmed with complexity of the books on this subject? Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days! First part of this book introduces Python basics including: <br>•Data Structures like Pandas <br>•Foundational libraries like Numpy, Seaborn and Scikit-Learn Second part of this book shows you how to build predictive machine learning models step by step using techniques such as: <br>•Regression analysis <br>•Decision tree analysis <br>•Training and testing data models <br>•Tensor Flow, Keras and PyTorch <br>•Additional data science concepts like Classification Analysis, Clustering, Association Learning and Dimension Reduction The final part of the book provides a structured framework on how to solve real world problems using data science and how to structure your data science project. After reading this book you will be able to: <br>•Code in Python with confidence <br>•Build new machine learning models from scratch <br>•Know how to clean and prepare your data for analytics <br>•Speak confidently about statistical analysis techniques Data Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world! If you are on the fence about making the leap to a new and lucrative career, this is the book for you! What sets this book apart from other books on the topic of Python and Machine learning: <br>•Step by step code examples and explanation <br>•Complex concepts explained visually <br>•Real world applicability of the machine learning models introduced <br>•Bonus free code samples that you can try yourself without any prior experience in Python! ",
"urlid": "https://www.google.com"
},
"8": {
"title": "Machine Learning Make Your Own Recommender System",
"image": "Assets/ML & AI/Machine Learning Make Your Own Recommender System/RecSys.jpg",
"description": "Recommender systems are one of the most visible applications of machine learning and their uncanny ability to convert our unspoken actions into items we like is both addicting and concerning. Recommender systems, though, are here to stay and for anyone beginning their journey in data science, this is a lucrative space for future employment. This book will get you up and running with the basics as well as the steps to coding your own recommender system using Python. Exercises include predicting book recommendations, relevant house properties for online marketing purposes, and whether a user will click on an ad campaign. Is This Book Right For Me? The contents of this book is designed for beginners with some background knowledge of data science, including classical statistics and computing programming. If this is your first exposure to data science, you may want to spend a few hours to read my first book Machine Learning for Absolute Beginners before you get started here. What You Will Learn: <br>• How to set up a free and easy sandbox environment using Jupyter Notebook <br>• How to prepare your data for processing <br>• How to code a collaborative filtering model <br>• How to code a content-based filtering model <br>• How recommender systems are evaluated <br>• What you need to know about privacy & ethics <br>• What the future of Recommender Systems might look like ",
"urlid": "1jrqD1x75sz24TFCgiL709eAlCp-WAhnt"
},
"9": {
"title": "Machine learning for Absolute beginners",
"image": "Assets/ML & AI/Machine learning for Absolute beginners/mlintro.jpg",
"description": "Machine Learning for Absolute Beginners Second Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home. New Updated Edition This major new edition features many topics not covered in the First Edition, including Cross Validation, Ensemble Modeling, Grid Search, Feature Engineering, and One-hot Encoding. Please note that this book is not a sequel to the First Edition but rather a restructured and revamped version of the First Edition. Readers of the First Edition should not feel compelled to purchase this Second Edition. Disclaimer: If you have passed the 'beginner' stage in your study of machine learning and are ready to tackle coding and deep learning, you would be well served with a long-format textbook. If, however, you are yet to reach that Lion King moment - as a fully grown Simba looking over the Pride Lands of Africa - then this is the book to gently hoist you up and offer you a clear lay of the land. In This Step-By-Step Guide You Will Learn: <br>• How to download free datasets <br>• What tools and machine learning libraries you need <br>• Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data <br>• Preparing data for analysis, including k-fold Validation <br>• Regression analysis to create trend lines <br>• Clustering, including k-means clustering, to find new relationships <br>• The basics of Neural Networks <br>• Bias/Variance to improve your machine learning model <br>• Decision Trees to decode classification <br>• How to build your first Machine Learning Model to predict house values using Python ",
"urlid": "1Ct9rcBnbbbKciR3Xdk8ls782N25tpSlc"
},
"10": {
"title": "The Hundred-Page Machine Learning Book",
"image": "Assets/ML & AI/The Hundred-Page Machine Learning Book/HPMLB.jpg",
"description": "Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: \"Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics \u2014 both theory and practice \u2014 that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field.\"\r Aur\u00e9lien G\u00e9ron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: \"The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn't hesitate to go into the math equations: that's one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field.\"\r Karolis Urbonas, Head of Data Science at Amazon: \"A great introduction to machine learning from a world-class practitioner.\"\r Chao Han, VP, Head of R&D at Lucidworks: \"I wish such a book existed when I was a statistics graduate student trying to learn about machine learning.\"\r Sujeet Varakhedi, Head of Engineering at eBay: \"Andriy's book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page.''\r Deepak Agarwal, VP of Artificial Intelligence at LinkedIn: \"A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time.''\r Vincent Pollet, Head of Research at Nuance: \"The Hundred-Page Machine Learning Book is an excellent read to get started with Machine Learning.''\r Gareth James, Professor of Data Sciences and Operations, co-author of the bestseller An Introduction to Statistical Learning, with Applications in R: \"This is a compact \u201chow to do data science\u201d manual and I predict it will become a go-to resource for academics and practitioners alike. At 100 pages (or a little more), the book is short enough to read in a single sitting. Yet, despite its length, it covers all the major machine learning approaches, ranging from classical linear and logistic regression, through to modern support vector machines, deep learning, boosting, and random forests. There is also no shortage of details on the various approaches and the interested reader can gain further information on any particular method via the innovative companion book wiki. The book does not assume any high level mathematical or statistical training or even programming experience, so should be accessible to almost anyone willing to invest the time to learn about these methods. It should certainly be required reading for anyone starting a PhD program in this area and will serve as a useful reference as they progress further. Finally, the book illustrates some of the algorithms using Python code, one of the most popular coding languages for machine learning. I would highly recommend \u201cThe Hundred-Page Machine Learning Book\u201d for both the beginner looking to learn more about machine learning and the experienced practitioner seeking to extend their knowledge base.\"\r \r ",
"urlid": "12rXpfJd1nlNeDOt97g4VJdm0vXqOv9V8"
},
"11": {
"title": "DEEP LEARNING with Python",
"image": "Assets/ML & AI/DEEP LEARNING with Python/deep learning.jpg",
"description": "Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran\u00c3\u00a7ois Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside <br>•\tDeep learning from first principles <br>•\tSetting up your own deep-learning environment <br>•\tImage-classification models <br>•\tDeep learning for text and sequences <br>•\tNeural style transfer, text generation, and image generation ",
"urlid": "1WuJRHFvUmoOvI6GegURdBQ7y0pe6oG8n"
},
"12": {
"title": "Java A Beginner’s Guide Eighth Edition",
"image": "Assets/Languages/Java A Beginner’s Guide Eighth Edition/Java.jpg",
"description": "Thoroughly updated for Java Platform Standard Edition 11, this hands-on resource shows, step by step, how to get started programming in Java from the very first chapter. Written by Java guru Herbert Schildt, the book starts with the basics, such as how to create, compile, and run a Java program. From there, you will learn essential Java keywords, syntax, and commands.\r Java: A Beginner's Guide, Eighth Edition covers the basics and touches on advanced features, including multithreaded programming, generics, Lambda expressions, and Swing. Enumeration, modules, and interface methods are also clearly explained. This Oracle Press guide delivers the appropriate mix of theory and practical coding necessary to get you up and running developing Java applications in no time.\r <br>•Clearly explains all of the new Java SE 11 features <br>•Features self-tests, exercises, and downloadable code samples <br>•Written by bestselling author and leading Java authority Herbert Schildt\r ",
"urlid": "1qzV3Qm8MbbGmjcyLC4HtZ4l3vGHgQxDP"
},
"13": {
"title": "Head First Kotlin A Brain-Friendly Guide",
"image": "Assets/Languages/Head First Kotlin A Brain-Friendly Guide/kotlin.jpg",
"description": "What will you learn from this book?\r Head First Kotlin is a complete introduction to coding in Kotlin. This hands-on book helps you learn the Kotlin language with a unique method that goes beyond syntax and how-to manuals and teaches you how to think like a great Kotlin developer. You\u2019ll learn everything from language fundamentals to collections, generics, lambdas, and higher-order functions. Along the way, you\u2019ll get to play with both object-oriented and functional programming. If you want to really understand Kotlin, this is the book for you.\r \r Why does this book look so different?\r Based on the latest research in cognitive science and learning theory, Head First Kotlin uses a visually rich format to engage your mind rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multisensory learning experience is designed for the way your brain really works\r ",
"urlid": "1U0EIqIxedt4jFDfl7g-1PJd0jdZYDoBH"
},
"14": {
"title": "Learn Python 3 the Hard Way",
"image": "Assets/Languages/Learn Python 3 the Hard Way/cover.jpg",
"description": "Zed Shaw has perfected the world\u2019s best system for learning Python 3. Follow it and you will succeed\u2014just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else.\r \r In Learn Python 3 the Hard Way, you\u2019ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you\u2019ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code\u2014live, as he\u2019s doing the exercises.\r <br>•\tInstall a complete Python environment\r <br>•\tOrganize and write code\r <br>•\tFix and break code\r <br>•\tBasic mathematics\r <br>•\tVariables\r <br>•\tStrings and text\r <br>•\tInteract with users\r <br>•\tWork with files\r <br>•\tLooping and logic\r <br>•\tData structures using lists and dictionaries\r <br>•\tProgram design\r <br>•\tObject-oriented programming\r <br>•\tInheritance and composition\r <br>•\tModules, classes, and objects\r <br>•\tPython packaging\r <br>•\tAutomated testing\r <br>•\tBasic game development\r <br>•\tBasic web development\r It\u2019ll be hard at first. But soon, you\u2019ll just get it\u2014and that will feel great! This course will reward you for every minute you put into it. Soon, you\u2019ll know one of the world\u2019s most powerful, popular programming languages. You\u2019ll be a Python programmer.\r \r This Book Is Perfect For\r <br>•\tTotal beginners with zero programming experience\r <br>•\tJunior developers who know one or two languages\r <br>•\tReturning professionals who haven\u2019t written code in years\r <br>•\tSeasoned professionals looking for a fast, simple, crash course in Python 3\r \r ",
"urlid": "1OvSB8xAMpjDlWT_txJJf-5WmzQSYtRM7"
},
"15": {
"title": "C# Programming in easy steps",
"image": "Assets/Languages/C hash Programming in easy steps/C hash programming.jpg",
"description": "C# is undeniably one of the most versatile programming languages available to engineers today. With this comprehensive guide, you\u2019ll learn just how powerful the combination of C# and .NET can be. Author Ian Griffiths guides you through C# 8.0 fundamentals and techniques for building cloud, web, and desktop applications.\r \r Designed for experienced programmers, this book provides many code examples to help you work with the nuts and bolts of C#, such as generics, LINQ, and asynchronous programming features. You\u2019ll get up to speed on .NET Core and the latest C# 8.0 additions, including asynchronous streams, nullable references, pattern matching, default interface implementation, ranges and new indexing syntax, and changes in the .NET tool chain.\r \r * Discover how C# supports fundamental coding features, such as classes, other custom types, collections, and error handling\r \r * Learn how to write high-performance memory-efficient code with .NET Core\u2019s Span and Memory types\r \r * Query and process diverse data sources, such as in-memory object models, databases, data streams, and XML documents with LINQ\r \r * Use .NET\u2019s multithreading features to exploit your computer\u2019s parallel processing capabilities\r \r * Learn how asynchronous language features can help improve application responsiveness and scalability\r ",
"urlid": "1OZYp1zb_cFFdNlKMQlu6WHWhIiwZgXrw"
},
"16": {
"title": "Introduction to C++ Programming Concepts and Applications",
"image": "Assets/Languages/Introduction to C++ Programming Concepts and Applications/introtocpp.jpg",
"description": "Considering how many hours we spend with computers\u2014phones, laptops, even \u201csmart\u201d screens on our home appliances\u2014it\u2019s easy to feel like they control us. But, in fact, we control them. Or, we do if we know how to use them. That\u2019s what computer programming gets to the heart of: taking command of the most powerful, versatile, and productive machines ever invented. And among the array of programming languages designed to get computers doing exactly what we want, C++ ranks as one of the most efficient, powerful, and popular. ",
"urlid": "1ZeiH_-BTOm1xF8Y7KNC5QpClkg-Vbyo7"
},
"17": {
"title": "Beginning Ruby From Novice to Professional",
"image": "Assets/Languages/Beginning Ruby From Novice to Professional/ruby.jpg",
"description": "Learn the principles behind object-oriented programming and within a few chapters create a fully functional Ruby application. Youll also gain a basic understanding of many ancillary technologies such as databases, XML, web frameworks, and networking - some of which are needed as part of a fully functioning Ruby application.\r The new edition of this book provides the same excellent introduction to Ruby as the previous editions plus updates for the newest version of Ruby 2.3. This book can also be used as a textbook or companion to a textbook on beginning Ruby programming.\r The light and agile Ruby programming language remains a very popular open source scripting option for developers building todays web and even some enterprise applications. And, now, Ruby also has applications using the Raspberry Pi, popular among hobbyists and makers. Many former Java developers still use Ruby on Rails today, the most popular framework for building Ruby applications.\r ",
"urlid": "1BytsakqXeVxjKOwF7fhssoIjBBeZqy_z"
},
"18": {
"title": "Data Structures using C",
"image": "Assets/Data Structures and Algorithms/Data Structures using C/datastructures.jpg",
"description": "This second edition of Data Structures Using C has been developed to provide a comprehensive and consistent coverage of both the abstract concepts of data structures as well as the implementation of these concepts using C language. It begins with a thorough overview of the concepts of C programming followed by introduction of different data structures and methods to analyse the complexity of different algorithms. It then connects these concepts and applies them to the study of various data structures such as arrays, strings, linked lists, stacks, queues, trees, heaps, and graphs. The book utilizes a systematic approach wherein the design of each of the data structures is followed by algorithms of different operations that can be performed on them, and the analysis of these algorithms in terms of their running times. Each chapter includes a variety of end-chapter exercises in the form of MCQs with answers, review questions, and programming exercises to help readers test their knowledge ",
"urlid": "1wjw0MMCZXaJmF-4bwPWJ9D9TQUQY5jq4"
},
"19": {
"title": "40 Algorithms Every Programmer should know",
"image": "Assets/Data Structures and Algorithms/40 Algorithms Every Programmer should know/40algos.jpg",
"description": "Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental algorithms, such as sorting and searching, to modern algorithms used in machine learning and cryptography\r Key Features\r <br>•\tLearn the techniques you need to know to design algorithms for solving complex problems\r <br>•\tBecome familiar with neural networks and deep learning techniques\r <br>•\tExplore different types of algorithms and choose the right data structures for their optimal implementation\r Book Description\r Algorithms have always played an important role in both the science and practice of computing. Beyond traditional computing, the ability to use algorithms to solve real-world problems is an important skill that any developer or programmer must have. This book will help you not only to develop the skills to select and use an algorithm to solve real-world problems but also to understand how it works.\r You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, such as searching and sorting, with the help of practical examples. As you advance to a more complex set of algorithms, you'll learn about linear programming, page ranking, and graphs, and even work with machine learning algorithms, understanding the math and logic behind them. Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.\r By the end of this book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.\r What you will learn\r <br>•\tExplore existing data structures and algorithms found in Python libraries\r <br>•\tImplement graph algorithms for fraud detection using network analysis\r <br>•\tWork with machine learning algorithms to cluster similar tweets and process Twitter data in real time\r <br>•\tPredict the weather using supervised learning algorithms\r <br>•\tUse neural networks for object detection\r <br>•\tCreate a recommendation engine that suggests relevant movies to subscribers\r <br>•\tImplement fool proof security using symmetric and asymmetric encryption on Google Cloud Platform (GCP)\r Who this book is for\r This book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code. Whether you are a beginner looking to learn the most commonly used algorithms in a clear and concise way or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful. Although Python programming experience is a must, knowledge of data science will be helpful but not necessary.\r ",
"urlid": "1FId4yWoIUdZGt0yHWE2u9pvNbkEpg4oS"
},
"20": {
"title": "Design and Analysis of Data Structures",
"image": "Assets/Data Structures and Algorithms/Design and Analysis of Data Structures/DAdataStructures.jpg",
"description": "This is a print companion to the Massive Open Online Course (MOOC), Data Structures: An Active Learning Approach (https://www.edx.org/course/data-structures-an-active-learning-approach), which utilizes the Active Learning approach to instruction, meaning it has various activities embedded throughout to help stimulate your learning and improve your understanding of the materials we will cover. While this print companion contains all STOP and Think questions, which will help you reflect on the material, and all Exercise Breaks, which will test your knowledge and understanding of the concepts discussed, we recommend utilizing the MAIT for all Code Challenges, which will allow you to actually implement some of the algorithms we will cover. ",
"urlid": "1Ff-U4tG9XIgebC5BEmB07DxZVACWvxlZ"
},
"21": {
"title": "Introduction to the Design and Analysis of Algorithms",
"image": "Assets/Data Structures and Algorithms/Introduction to the Design and Analysis of Algorithms/introtoDAA.jpg",
"description": "Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal treatment while thoroughly covering the material required in an introductory algorithms course. Popular puzzles are used to motivate students' interest and strengthen their skills in algorithmic problem solving. Other learning-enhancement features include chapter summaries, hints to the exercises, and a detailed solution manual. ",
"urlid": "1Jg8tLE_MuS9M70yhqTlRO8ex1_MZFsSV"
},
"22": {
"title": "Analysis And Design of Algorithms",
"image": "Assets/Data Structures and Algorithms/Analysis And Design of Algorithms/ADA.jpg",
"description": "Analysis and Design of Algorithms provides a structured view of algorithm design techniques in a concise, easy-to-read manner. The book begins with a clear explanation of the basics: what algorithms are, their practical applications, asymptotic notation, and data structures. The second section covers the algorithmic design techniques of divide and conquer, greedy, dynamic programming, branch and bound, and graph traversal. For each of these techniques, the book presents templates and guidelines on when to use and not to use each technique. The third major section of the book covers NP-completeness and the inherent hardness of problems. Using the material provided in this book, students and professionals can master the processes to use in solving the most difficult algorithmic problems. Users can explore various techniques, and learn to decide which algorithm design technique to use for a given problem. Many sections contain innovative mnemonics to aid the readers in remembering the templates and key takeaways. ",
"urlid": "1_U_Ojx9ok9SV1J2ceDxwov5I5SlRPSbb"
},
"23": {
"title": "Learning Algorithms Through Programming and Puzzle Solving",
"image": "Assets/Data Structures and Algorithms/Learning Algorithms Through Programming and Puzzle Solving/LATPPS.jpg",
"description": "Analysis and Design of Algorithms provides a structured view of algorithm design techniques in a concise, easy-to-read manner. The book begins with a clear explanation of the basics: what algorithms are, their practical applications, asymptotic notation, and data structures. The second section covers the algorithmic design techniques of divide and conquer, greedy, dynamic programming, branch and bound, and graph traversal. For each of these techniques, the book presents templates and guidelines on when to use and not to use each technique. The third major section of the book covers NP-completeness and the inherent hardness of problems. Using the material provided in this book, students and professionals can master the processes to use in solving the most difficult algorithmic problems. Users can explore various techniques, and learn to decide which algorithm design technique to use for a given problem. Many sections contain innovative mnemonics to aid the readers in remembering the templates and key takeaways. ",
"urlid": "1HRFHIHAEmtZeFPy_2ntr2rFKZyG2CWfb"
},
"24": {
"title": "Data Analytics using Python",
"image": "Assets/Data Science/Data Analytics using Python/DataanalyticsPy.jpg",
"description": "Data is the fuel of 21st century. The advanced technological development has brought a massive increase in the volume and spectrum of data by including text, image and video data. Data analytics using Python aims to make readers understand the applications of analytics in different domains with proper code and explanation. The book starts from basics of Python and gradually increases its level to machine learning. Significant focus has also been laid on deep learning and applications \u2013 neural network models like mlp, rnn and CNN; trained models for text and image data and development of chatbots. ",
"urlid": "https://www.google.com"
},
"25": {
"title": "Essentials of R for Data Analytics",
"image": "Assets/Data Science/Essentials of R for Data Analytics/Rdataanalytics.jpg",
"description": "With widespread and exponential growth of data, people with data science background are in great demand. Data analytics, a subdomain of data science, is meant to turn data into insight and actionable knowledge. Data analytics mainly deals with exploring, visualizing, transforming and modelling data for making predictions. Learning R is an essential step towards becoming a data analyst. ",
"urlid": "https://www.google.com"
},
"26": {
"title": "Data Science Stratagies for dummies",
"image": "Assets/Data Science/Data Science Stratagies for dummies/DSforDummies.jpg",
"description": "All the answers to your data science questions\r Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the \u201cwhat\u201d and the \u201cwhy\u201d of data science and covering what it takes to lead and nurture a top-notch team of data scientists.\r With this book, you\u2019ll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data.\r <br>•\tLearn exactly what data science is and why it\u2019s important\r <br>•\tAdopt a data-driven mindset as the foundation to success\r <br>•\tUnderstand the processes and common roadblocks behind data science\r <br>•\tKeep your data science program focused on generating business value\r <br>•\tNurture a top-quality data science team\r In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value.\r \r ",
"urlid": "1E1eUHVLQknVyc8CuNs8Zvw1klmww6e0a"
},
"27": {
"title": "Data Science Projects With Python",
"image": "Assets/Data Science/Data Science Projects With Python/DSPpy.jpg",
"description": "Data analysis is the method of examining, cleansing, and modelling with the objective of determining useful information for effective decision-making and operations. It includes diverse techniques and tools and plays a major role in different business, Science and Social Science areas. R software provides numerous functions and packages for using different techniques for producing desired outcome. Data analytics with R will enable readers gain sufficient knowledge and experience to perform analysis using different analytical tools available in R. Each Chapter begins with a number of important and interesting examples taken from a variety of sectors ",
"urlid": "https://www.google.com"
},
"28": {
"title": "Python Data Science Handbook",
"image": "Assets/Data Science/Python Data Science Handbook/DShandbookPy.jpg",
"description": "For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all-IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.\r Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.\r With this handbook, you’ll learn how to use:\r <br>•\tIPython and Jupyter: provide computational environments for data scientists using Python\r <br>•\tNumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python\r <br>•\tPandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python\r <br>•\tMatplotlib: includes capabilities for a flexible range of data visualizations in Python\r <br>•\tScikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms\r \r ",
"urlid": "1BjnwTp66g-ETPwU7lFUzcxbYUpp5E63n"
},
"29": {
"title": "Data Analytics with R",
"image": "Assets/Data Science/Data Analytics with R/Data Analytics with R.jpg",
"description": "Data analysis is the method of examining, cleansing, and modelling with the objective of determining useful information for effective decision-making and operations. It includes diverse techniques and tools and plays a major role in different business, Science and Social Science areas. R software provides numerous functions and packages for using different techniques for producing desired outcome. Data analytics with R will enable readers gain sufficient knowledge and experience to perform analysis using different analytical tools available in R. Each Chapter begins with a number of important and interesting examples taken from a variety of sectors ",
"urlid": "https://www.google.com"
}
}