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were 'Game-based learning', 'GBL', 'Programming', 'Programming education', ' Learning games', 'Educational games' and 'Python'. This study is also shared as ...
Publisher: Academic Conferences and publishing limited
This book moves fluently between the theoretical principles of machine learning and the practical details of implementation with Python.
Author: Sebastian Raschka
Publisher: Packt Publishing Ltd
Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most powerful Python libraries to implement machine learning and deep learning Get to know the best practices to improve and optimize your machine learning systems and algorithms Who This Book Is For If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential and unmissable resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for developers and data scientists who want to teach computers how to learn from data. What You Will Learn Understand the key frameworks in data science, machine learning, and deep learning Harness the power of the latest Python open source libraries in machine learning Explore machine learning techniques using challenging real-world data Master deep neural network implementation using the TensorFlow library Learn the mechanics of classification algorithms to implement the best tool for the job Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Delve deeper into textual and social media data using sentiment analysis In Detail Machine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka's bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The scikit-learn code has also been fully updated to include recent improvements and additions to this versatile machine learning library. Sebastian Raschka and Vahid Mirjalili's unique insight and expertise introduce you to machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. By the end of the book, you'll be ready to meet the new data analysis opportunities in today's world. If you've read the first edition of this book, you'll be delighted to find a new balance of classical ideas and modern insights into machine learning. Every chapter has been critically updated, and there are new chapters on key technologies. You'll be able to learn and work with TensorFlow more deeply than ever before, and get essential coverage of the Keras neural network library, along with the most recent updates to scikit-learn. Style and Approach Python Machine Learning Second Edition takes a practical, hands-on coding approach so you can learn about machine learning by coding with Python. This book moves fluently between the theoretical principles of machine learning and the practical details of implementation with Python.
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 basics of syntax, but it condenses years of experience. You will learn warts, gotchas, best practices and hints that have been gleaned through the years in days. You will hit the ground running and running in the right way.Learn Python QuicklyPython is an incredible language. It is powerful and applicable in many areas. It is used for automation of simple or complex tasks, numerical processing, web development, interactive games and more. Whether you are a programmer coming to Python from another language, managing Python programmers or wanting to learn to program, it makes sense to cut to the chase and learn Python the right way. You could scour blogs, websites and much longer tomes if you have time. Treading on Python lets you learn the hints and tips to be Pythonic quickly.Packed with Useful Hints and TipsYou'll learn the best practices without wasting time searching or trying to force Python to be like other languages. I've collected all the gems I've gleaned over years of writing and teaching Python for you.A No Nonsense Guide to Mastering Basic PythonPython is a programming language that lets you work more quickly and integrate your systems more effectively. You can learn to use Python and see almost immediate gains in productivity and lower maintenance costs.What you will learn: Distilled best practices and tips How interpreted languages work Using basic types such as Strings, Integers, and Floats Best practices for using the interpreter during development The difference between mutable and immutable data Sets, Lists, and Dictionaries, and when to use each Gathering keyboard input How to define a class Looping constructs Handling Exceptions in code Slicing sequences Creating modular code Using libraries Laying out code Community prescribed conventions
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around youAbout This Book- Step into the amazing world of intelligent apps using this comprehensive guide- Enter the world of ...
Author: Prateek Joshi
Build real-world AI applications with Python to intelligently interact with your surroundingsAbout This Book* Step into the amazing world of intelligent apps using this comprehensive guide* Enter the world of AI, explore it, and become independent to create your own AI apps* Work through simple yet insightful examples that will get you up and running with artificial intelligence in no timeWho This Book Is ForThis book is for Python developers who want to build real-world AI applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to implement AI techniques in their existing technology stacks.What You Will Learn* Find out how to use different classification and regression techniques* Understand the concept of clustering and how to use it to automatically segment data* See how to build an intelligent recommender system* Understand logic programming and how to use it* Develop automatic speech recognition systems* Understand the basics of heuristic search and genetic programming* Develop an understanding of reinforcement learning* Discover how to build AI applications centered on images, text, and time series data* Understand how to use deep learning algorithms and build applications based on itIn DetailAI is becoming increasingly relevant in the modern world where the ecosystem is driven by technology and data. AI is used extensively across many fields such as robotics, computer vision, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various AI algorithms that can be used to build various applications.During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of the AI concepts, you will learn how to develop the various building blocks of AI using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application based on images, text, stock market, or some other form of data, this exciting book on AI will definitely guide you all the way!
Example >>>tup1 = (“R Programming”, “Python”, 2017, 2018) >>>tup2 = (1, 2, 3,
4) >>>print(“tup1: “, tup1) >>>print(“tup2[1:5]: “, tup2[1:5]) If we execute the program, the output follows like this Tup1 : R Programming Tup2[1:5]: [2, 3, 4]
Author: A Krishna Mohan et al.
Publisher: S. Chand Publishing
This book contains in-depth knowledge of "Python with Machine Learning". This book is written in a logical and sequential, outputs with print screen, modules for systematic development of the subject. This book is covered for all the students those who are interested to learn programming on Python and Machine learning. Each and Every program along with example is executed practically. This book is aimed at emerging trends in Technology, development all over the Globe and even corporate people also will learn all the topics. Each topic is explained very simple and given a lot of example with syntax. It has been written in an articulate manner and is packed with practical approach target for all students of Undergraduate, Graduate, of Computer Science and Engineering (M.Tech, M.C.A, M.Sc (CS, IT) B.Tech), Research Scholar and Corporate Employees those who are new to this area.
Python Programming for Beginners features: No coding experience needed!--Designed just for kids, this Python programming book is filled with step-by-step directions, simple explanations, and detailed code breakdowns.
With this Learning Path, you will gain complete knowledge to solve problems by building high performing applications loaded with asynchronous, multithreaded code and proven design patterns.
Author: Dr. Gabriele Lanaro
Publisher: Packt Publishing Ltd
Create distributed applications with clever design patterns to solve complex problems Key Features Set up and run distributed algorithms on a cluster using Dask and PySpark Master skills to accurately implement concurrency in your code Gain practical experience of Python design patterns with real-world examples Book Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: Python High Performance - Second Edition by Gabriele Lanaro Mastering Concurrency in Python by Quan Nguyen Mastering Python Design Patterns by Sakis Kasampalis What you will learn Use NumPy and pandas to import and manipulate datasets Achieve native performance with Cython and Numba Write asynchronous code using asyncio and RxPy Design highly scalable programs with application scaffolding Explore abstract methods to maintain data consistency Clone objects using the prototype pattern Use the adapter pattern to make incompatible interfaces compatible Employ the strategy pattern to dynamically choose an algorithm Who this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.
Author: Pradeeban KathiraveluPublish On: 2017-08-09
Discover practical solutions for a wide range of real-world network programming tasks About This Book Solve real-world tasks in the area of network programming, system/networking administration, network monitoring, and more.
Author: Pradeeban Kathiravelu
Publisher: Packt Publishing Ltd
Discover practical solutions for a wide range of real-world network programming tasks About This Book Solve real-world tasks in the area of network programming, system/networking administration, network monitoring, and more. Familiarize yourself with the fundamentals and functionalities of SDN Improve your skills to become the next-gen network engineer by learning the various facets of Python programming Who This Book Is For This book is for network engineers, system/network administrators, network programmers, and even web application developers who want to solve everyday network-related problems. If you are a novice, you will develop an understanding of the concepts as you progress with this book. What You Will Learn Develop TCP/IP networking client/server applications Administer local machines' IPv4/IPv6 network interfaces Write multi-purpose efficient web clients for HTTP and HTTPS protocols Perform remote system administration tasks over Telnet and SSH connections Interact with popular websites via web services such as XML-RPC, SOAP, and REST APIs Monitor and analyze major common network security vulnerabilities Develop Software-Defined Networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX Controllers Emulate simple and complex networks with Mininet and its extensions for network and systems emulations Learn to configure and build network systems and Virtual Network Functions (VNF) in heterogeneous deployment environments Explore various Python modules to program the Internet In Detail Python Network Programming Cookbook - Second Edition highlights the major aspects of network programming in Python, starting from writing simple networking clients to developing and deploying complex Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) systems. It creates the building blocks for many practical web and networking applications that rely on various networking protocols. It presents the power and beauty of Python to solve numerous real-world tasks in the area of network programming, network and system administration, network monitoring, and web-application development. In this edition, you will also be introduced to network modelling to build your own cloud network. You will learn about the concepts and fundamentals of SDN and then extend your network with Mininet. Next, you'll find recipes on Authentication, Authorization, and Accounting (AAA) and open and proprietary SDN approaches and frameworks. You will also learn to configure the Linux Foundation networking ecosystem and deploy and automate your networks with Python in the cloud and the Internet scale. By the end of this book, you will be able to analyze your network security vulnerabilities using advanced network packet capture and analysis techniques. Style and approach This book follows a practical approach and covers major aspects of network programming in Python. It provides hands-on recipes combined with short and concise explanations on code snippets. This book will serve as a supplementary material to develop hands-on skills in any academic course on network programming. This book further elaborates network softwarization, including Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and orchestration. We learn to configure and deploy enterprise network platforms, develop applications on top of them with Python.
Coding All-in-One For Dummies gives you an ideal place to start when you're ready to add this valuable asset to your professional repertoire.
Author: Nikhil Abraham
Publisher: John Wiley & Sons
See all the things coding can accomplish The demand for people with coding know-how exceeds the number of people who understand the languages that power technology. Coding All-in-One For Dummies gives you an ideal place to start when you're ready to add this valuable asset to your professional repertoire. Whether you need to learn how coding works to build a web page or an application or see how coding drives the data revolution, this resource introduces the languages and processes you'll need to know. Peek inside to quickly learn the basics of simple web languages, then move on to start thinking like a professional coder and using languages that power big applications. Take a look inside for the steps to get started with updating a website, creating the next great mobile app, or exploring the world of data science. Whether you're looking for a complete beginner's guide or a trusted resource for when you encounter problems with coding, there's something for you! Create code for the web Get the tools to create a mobile app Discover languages that power data science See the future of coding with machine learning tools With the demand for skilled coders at an all-time high, Coding All-in-One For Dummies is here to propel coding newbies to the ranks of professional programmers.
This Book Is Perfect For Total beginners with zero programming experience Junior developers who know one or two languages Returning professionals who haven’t written code in years Seasoned professionals looking for a fast, simple, crash ...
Author: Zed A. Shaw
Publisher: Addison-Wesley Professional
You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Python 3 the Hard Way, you’ll 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’ll 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—live, as he’s doing the exercises. Install a complete Python environment Organize and write code Fix and break code Basic mathematics Variables Strings and text Interact with users Work with files Looping and logic Data structures using lists and dictionaries Program design Object-oriented programming Inheritance and composition Modules, classes, and objects Python packaging Automated testing Basic game development Basic web development It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Python programmer. This Book Is Perfect For Total beginners with zero programming experience Junior developers who know one or two languages Returning professionals who haven’t written code in years Seasoned professionals looking for a fast, simple, crash course in Python 3
The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses.
Author: Laura Igual
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
The book also demonstrates the benefit of using a debugger to inspect the state of a program while it is executing.
Author: Kent D. Lee
This easy-to-follow and classroom-tested textbook guides the reader through the fundamentals of programming with Python, an accessible language which can be learned incrementally. Features: incudes numerous examples and practice exercises throughout the text, with additional exercises, solutions and review questions at the end of each chapter; highlights the patterns which frequently appear when writing programs, reinforcing the application of these patterns for problem-solving through practice exercises; introduces the use of a debugger tool to inspect a program, enabling students to discover for themselves how programs work and enhance their understanding; presents the Tkinter framework for building graphical user interface applications and event-driven programs; provides instructional videos and additional information for students, as well as support materials for instructors, at an associated website.
This book 'Introduction to Computing and Problem Solving with Python' will help every student,teacher and researcher to understand the computing basics and advanced PythonProgramming language.
Author: Jeeva Jose
Publisher: KHANNA PUBLISHING
This book 'Introduction to Computing and Problem Solving with Python' will help every student,teacher and researcher to understand the computing basics and advanced PythonProgramming language. The Python programming topics include the reserved keywords,identifiers, variables, operators, data types and their operations, flowcontrol techniques which include decision making and looping, modules, filesand exception handling techniques. Advanced topics like Python regularexpressions, Database Programming and Object Oriented Programming concepts arealso covered in detail. All chapters have worked out programs, illustrations,review and frequently asked interview questions. The simple style of presentationmakes this a friend for self-learners. More than 300 solved lab exercisesavailable in this book is tested in Python 3.4.3 version for Windows. The book covers syllabus for more than 35 International Universities and45 Indian universities like Dr. APJ Abdul Kalam Technological University,Christ University, Savitribai Phule Pune University, University of Delhi, University of Calicut, Mahatma Gandhi University, University of Mumbai, AICTE, CBSE, MIT, University of Virginia, University of Chicago, University of Toronto, Technical University of Denmark etc.
Michael L Littman. Markov games as a framework for multi-agent reinforcement learning. ... In Advances in Neural Information Processing Systems, pages 6379–
6390, 2017. 224 432. Mark Lutz. Programming Python, volume 8. O'Reilly, 1996.
Author: Aske Plaat
Publisher: Springer Nature
In this textbook the author takes as inspiration recent breakthroughs in game playing to explain how and why deep reinforcement learning works. In particular he shows why two-person games of tactics and strategy fascinate scientists, programmers, and game enthusiasts and unite them in a common goal: to create artificial intelligence (AI). After an introduction to the core concepts, environment, and communities of intelligence and games, the book is organized into chapters on reinforcement learning, heuristic planning, adaptive sampling, function approximation, and self-play. The author takes a hands-on approach throughout, with Python code examples and exercises that help the reader understand how AI learns to play. He also supports the main text with detailed pointers to online machine learning frameworks, technical details for AlphaGo, notes on how to play and program Go and chess, and a comprehensive bibliography. The content is class-tested and suitable for advanced undergraduate and graduate courses on artificial intelligence and games. It's also appropriate for self-study by professionals engaged with applications of machine learning and with games development. Finally it's valuable for any reader engaged with the philosophical implications of artificial and general intelligence, games represent a modern Turing test of the power and limitations of AI.
Style and approach This book will be your comprehensive guide to learning the various data mining techniques and implementing them in Python.
Author: Robert Layton
Publisher: Packt Publishing Ltd
Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using Deep Neural Networks, and create insightful predictive models. About This Book Use a wide variety of Python libraries for practical data mining purposes. Learn how to find, manipulate, analyze, and visualize data using Python. Step-by-step instructions on data mining techniques with Python that have real-world applications. Who This Book Is For If you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected. What You Will Learn Apply data mining concepts to real-world problems Predict the outcome of sports matches based on past results Determine the author of a document based on their writing style Use APIs to download datasets from social media and other online services Find and extract good features from difficult datasets Create models that solve real-world problems Design and develop data mining applications using a variety of datasets Perform object detection in images using Deep Neural Networks Find meaningful insights from your data through intuitive visualizations Compute on big data, including real-time data from the internet In Detail This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations. Style and approach This book will be your comprehensive guide to learning the various data mining techniques and implementing them in Python. A variety of real-world datasets is used to explain data mining techniques in a very crisp and easy to understand manner.
Topics such as generators and coroutines are often misunderstood and these are explained in detail, whilst topics such as Referential Transparency, multiple inheritance and exception handling are presented using examples.
Author: John Hunt
This textbook on Python 3 explains concepts such as variables and what they represent, how data is held in memory, how a for loop works and what a string is. It also introduces key concepts such as functions, modules and packages as well as object orientation and functional programming. Each section is prefaced with an introductory chapter, before continuing with how these ideas work in Python. Topics such as generators and coroutines are often misunderstood and these are explained in detail, whilst topics such as Referential Transparency, multiple inheritance and exception handling are presented using examples. A Beginners Guide to Python 3 Programming provides all you need to know about Python, with numerous examples provided throughout including several larger worked case studies illustrating the ideas presented in the previous chapters.
This book is perfect for you: * If you're coming to Python from another programming language * If you're learning Python as a first programming language * If you're looking to increase the readability, maintainability, and correctness of ...
Author: Jeff Knupp
Publisher: Jeff Knupp
The "Writing Idiomatic Python" book is finally here! Chock full of code samples, you'll learn the "Pythonic" way to accomplish common tasks. Each idiom comes with a detailed description, example code showing the "wrong" way to do it, and code for the idiomatic, "Pythonic" alternative. *This version of the book is for Python 3.3+. There is also a Python 2.7.3+ version available.* "Writing Idiomatic Python" contains the most common and important Python idioms in a format that maximizes identification and understanding. Each idiom is presented as a recommendation to write some commonly used piece of code. It is followed by an explanation of why the idiom is important. It also contains two code samples: the "Harmful" way to write it and the "Idiomatic" way. * The "Harmful" way helps you identify the idiom in your own code. * The "Idiomatic" way shows you how to easily translate that code into idiomatic Python. This book is perfect for you: * If you're coming to Python from another programming language * If you're learning Python as a first programming language * If you're looking to increase the readability, maintainability, and correctness of your Python code What is "Idiomatic" Python? Every programming language has its own idioms. Programming language idioms are nothing more than the generally accepted way of writing a certain piece of code. Consistently writing idiomatic code has a number of important benefits: * Others can read and understand your code easily * Others can maintain and enhance your code with minimal effort * Your code will contain fewer bugs * Your code will teach others to write correct code without any effort on your part
These concepts are necessary to understand every other aspect of the scripting language. By reading this book, you're off to a great start. It is designed to ease your way into Python programming world.
Author: Alan Grid
Take Advantage of 55% Book Store Discount Win the Trust of Your Clients with this Professional Book Why Python has been proclaimed by the most Professional Techs as the best Scripting Language ? Do you want to learn Coding from scratch? Python is presumably the easiest-to-learn and nicest-to-use programming language in widespread use. Python code is clear to read and write, and it is short without being cryptic. It is a very powerful language, which means that we can generally write far fewer lines of Python code than would be needed for an equivalent application written in, say, C++ or Java. Python is typically typed in an implicit and dynamic format; hence, there is no requirement to declare variables. These types are enforced, and the variables are sensitive to cases. There is no definite array of characters used to terminate statements in Python. Any statement which expects a level of indentation is concluded using a colon sign. Multiple variables can also be used on a single line. This book covers the following topics: - The 7 main Features of Python - Why you should use Python - What is the best Python web app framework and why - Data Types in Python - Conditional Statements - Why is Python so popular in Machine Learning - ...&Lot more! In Python Programming, the English language is mainly used in coding many keywords. The mastery of these keywords means knowledge of the fundamental aspects of python programming. However, before delving into these primary keywords, you have to understand the basic concepts associated with Python. These concepts are necessary to understand every other aspect of the scripting language. By reading this book, you're off to a great start. It is designed to ease your way into Python programming world. So, Ready to Become a Master of Python? Get Customers Addicted to Your Store!
Figure 2.1 CT components (Romero et al., 2017a). ... a virtual programming
composing and runs annual ... After being mentored and tutored by a filmmaker,
a group of adolescent girls have learned to code using a donated laptop, created
an app for ...
Author: Linda Daniela
Epistemological Approaches to Digital Learning in Educational Contexts is dedicated to topical issues in school education and pedagogical science related to the learning process in a technology and media enriched environment. It opens up discussions on the development of the educational science sector and strategies for smart pedagogy to promote synergy between technology and pedagogy to support students in the learning process. The book presents different perspectives on how to evaluate the enhancement of technology use, which can help improve Computational Thinking skills. It also helps in identifying the changes in pupils’ algorithmic thinking through programming in Scratch 2.0. The book further explores the way digitally-mediated materiality may support teaching practice and proposes tools that are available for the educational curator in a digital learning environment. This book will be of great interest to academics, researchers, and post-graduate students in the fields of higher education, vocational education, and digital learning.