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Python is a robust, procedural, object-oriented, and functional language. The features of the language make it valuable for web development, game development, business, and scientific programming. This book deals with problem-solving and programming in Python. It concentrates on the development of efficient algorithms, the syntax of the language, and the ability to design programs in order to solve problems. In addition to standard Python topics, the book has extensive coverage of NumPy, data visualization, and Matplotlib. Numerous types of exercises, including theoretical, programming, and multiple-choice, reinforce the concepts covered in each chapter. FEATURES:Concentrates on the development of efficient algorithms, the syntax of the language, and theability to design programs in order to solve problemsFeatures both standard Python topics and also extensive coverage of NumPy, data visualization, and Matplotlib problem-solving techniques

Computer. Automation --- Python (Computer program language)

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Discover clean ways to write code that will run on both Python 2 and 3.This book is tutorial-oriented with detailed examples of how to convert existing Python 2-compatible code to code that will run reliably on both Python 2 and 3. Although Python 3 is considered the future of Python, Python 2.x will be maintained for several more years, alongside Python 3, which is not backwards compatible. For those who need to support both versions, this book guides you through the process. Python 2 and 3 Compatibility explains the syntactical differences between Python 2 and 3, and how to use Python packages Python-Future and Six to implement neutral compatibility. Developers working on either small, medium, or large projects will appreciate the author's clear explanations, detailed examples, and clean techniques to help them extend support for both versions to their existing Python 2-compatible projects.

Programming --- Python (informatica) --- Python (Computer program language). --- Python.

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This book, which is designed for middle-school through college-aged students, will arm beginners with solid programming foundations they can carry throughout life. It uses fun and simple language (and programming examples) to teach the fundamentals needed to start the down path of becoming a programmer. Python is a highly flexible language, allowing developers to enter any number of technical fields and is a welcome addition to any resume. With its low learning curve, it makes a great introductory language, as new developers can take the coding fundamentals they learn in Python and apply them to any other language. The second edition builds upon the foundation of the first book, revising all the chapters where the language has changed, updating the commands, code, and examples to bring it up to date with the current version of Python. Since Python is the most popular programming language in the world and can be used in conjunction with other languages - across multiple platforms - it can increase the reader's ability to qualify for a wider range of jobs than other languages. Finally, Python is fun - something not every programming language can boast! You will: Install and configure Python Grasp basic software development principles and syntax Understand the best practices for coding in Python Create applications and debug code.

Programming --- Python (informatica) --- programmeertalen --- Python (Computer program language)

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Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms. Care is taken to walk you through the principles of machine learning through clear examples written in Python that you can try out and experiment with at home on your own machine. All applied math and programming skills required to master the content are covered in this book. In-depth knowledge of object-oriented programming is not required as working and complete examples are provided and explained. Coding examples are in-depth and complex when necessary. They are also concise, accurate, and complete, and complement the machine learning concepts introduced. Working the examples helps to build the skills necessary to understand and apply complex machine learning algorithms. Hands-on Scikit-Learn for Machine Learning Applications is an excellent starting point for those pursuing a career in machine learning. Students of this book will learn the fundamentals that are a prerequisite to competency. Readers will be exposed to the Anaconda distribution of Python that is designed specifically for data science professionals, and will build skills in the popular Scikit-Learn library that underlies many machine learning applications in the world of Python. What You'll Learn Work with simple and complex datasets common to Scikit-Learn Manipulate data into vectors and matrices for algorithmic processing Become familiar with the Anaconda distribution used in data science Apply machine learning with Classifiers, Regressors, and Dimensionality Reduction Tune algorithms and find the best algorithms for each dataset Load data from and save to CSV, JSON, Numpy, and Pandas formats.

Programming --- Information systems --- Python (informatica) --- programmeren (informatica) --- gegevensanalyse --- Machine learning. --- Python (Computer program language). --- Big data. --- Machine Learning. --- Python. --- Big Data. --- Python (Computer program language)

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Cognitive Virtual Bots are taking the technology and user experience world by storm. This book provides clear guidance on how different cognitive platforms can be used to develop Cognitive Virtual Assistants that enable a conversation by using DialogFlow and advanced Natural Language Processing. You will start by understanding the technology landscape and various use cases that Cognitive Virtual Assistants can be used in. Early chapters will take you through the basics of Cognitive Virtual Assistants, before moving onto advanced concepts and hands on examples of using IBM Watson Assistant and its advanced configurations with Watson Discovery Services, Watson Knowledge Studio and Spellchecker Service. You'll then examine integrations that enrich the Cognitive Virtual Assistant by providing data around weather, locations, stock markets. The book concludes with a glimpse of what to expect in the future for Cognitive Virtual Assistants. You will: Review the fundamentals of Cognitive Virtual Assistants Develop a Cognitive Virtual Assistant from scratch using IBM Watson platform Integrate and enrich your Virtual Agent with other services such as weather, location and stocks Instantly deliver your bot on major messaging channels such as Skype, SMS, and Webchat Train your Cognitive Virtual Agent on specific use cases.

Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Python (informatica) --- KI (kunstmatige intelligentie) --- AI (artificiële intelligentie) --- Artificial intelligence. --- Python (Computer program language). --- Artificial Intelligence. --- Python. --- Python (Computer program language)