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This best-selling guide to Prolog and Artificial Intelligence, which has been updated to include key developments in the field, concentrates on the art of using the basic mechanisms of Prolog to solve interesting AI problems.

• Combined approach to Prolog and AI allows flexibility for learning and teaching.
• Provides a thorough representation of AI, emphasizing practical techniques and Prolog implementations.
• Prolog programs for use in projects and research are available for download from the companion website http://www.pearsoned.co.uk/bratko

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Introduces the PostScript programming language, which is designed to describe and control the appearance of text, images, and graphic material for the printed page, and demonstrates useful techniques and procedures

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Introduces the PostScript document description language, shows how to manipulate text, graphics, and fonts, and explains the function of each operator

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[Jason Lengstorf, Thomas Blom Hansen] Php For Absolute Beginners

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Python is one of the most popular languages for data analysis and prediction. What's more, tensorflow and torch, useful tools of recent deep learning, are fully implemented by Python. The basic form of data in these languages is an array, created by Python's important package numpy. In particular, arrays are the basis of data science because they have structures of vectors and matrices that give the meaning of direction and magnitude to each value in the data set. For example, a matrix structure allows transformation to a simple form without losing the basic characteristics of a vast data set. These transformations are useful for...

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Put away your credentials and get prepared to immerse yourself in a basic crash course of data analysis, Pandas and Numpy even if you are a beginner with no knowledge about programming.

Python is a high-level programming language, released for the first time in 1991 by its creator Guido van Rossum, a Dutch programmer currently operating in Dropbox. Python is used by thousands of people to do things from the power of Instagram, to building video games with the PyGame library.

Often programming is seen as something complicated:
· we fear the effort that goes into learning a new programming language
· the books available on...

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Discounted at $ 23.95 instead of $ 39.95 for a few days with 55% OFF for Bookstores! LAST DAYS!! * Start Programming PythonWhat if you could make your program one that can learn by trial and error or based on the information you show?What if you could get a program that could adapt and change based on the user's input?And what if you were able to make all of this happen with the Python coding language, helping beginner's work with more complicated codes?This is all possible with Python machine learning.This guidebook will take some time to look at Python machine learning and all of the neat things that you can do with it.Machine...

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Virtual Machine technology applies the concept of virtualization to an entire machine, circumventing real machine compatibility constraints and hardware resource constraints to enable a higher degree of software portability and flexibility. Virtual machines are rapidly becoming an essential element in computer system design. They provide system security, flexibility, cross-platform compatibility, reliability, and resource efficiency. Designed to solve problems in combining and using major computer system components, virtual machine technologies play a key role in many disciplines, including operating systems, programming languages...

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Master today's required computer science topics while preparing for further study with Lambert's FUNDAMENTALS OF PYTHON: FIRST PROGRAMS. This book's easygoing approach is ideal, no matter what your background. The approach starts with simple algorithmic code and then scales into working with functions, objects, and classes as the problems become more complex and require new abstraction mechanisms. Rather than working only with numeric or text-based applications like other introductory texts, this edition presents graphics, image manipulation, GUIs, and simple networked client/server applications. The author uses Python's standard...

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The book you were waiting for to learn how to program with Python !
100% Beginners centered

• Introduction to Python
• Variables, Math expressions
• User input and conditional statements
• Comments, lists, tuple
• Dictionary, Loop, Changing case
• Functions, classes
• Data files, modules
• CSV files, JSON files
• Exceptions handling

So don't wait any longer and get this comprehensive guide to Python now !

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Master the art of using Python for a diverse range of network engineering tasks to thrive in the next era of networking

Key Features:​

• Unlock the power of Python libraries to tackle difficult network problems efficiently and effectively.
• Use Python for network device automation, DevOps, and software-defined networking
• Become an expert in implementing advanced network-related tasks with Python.

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Being able to automate and increase network change velocity has become critical to many businesses. Networks in your infrastructure is at the foundation of how your application can be deployed...

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Learn the art of regression analysis with Python

About This Book​

• Become competent at implementing regression analysis in Python
• Solve some of the complex data science problems related to predicting outcomes
• Get to grips with various types of regression for effective data analysis

Who This Book Is For​

The book targets Python developers, with a basic understanding of data science, statistics, and math, who want to learn how to do regression analysis on a dataset. It is beneficial if you have some knowledge of statistics and data science....

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Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you’ve gotten the hang of things.

Along the way, you’ll discover new ways to explore math and gain valuable programming skills that you’ll use throughout your study of math and computer science. Learn how to:
–Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots
–Explore set theory and probability...

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The Python Book

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The parameter estimation and hypothesis testing are the basic tools in statistical inference. These techniques occur in many applications of data processing., and methods of Monte Carlo have become an essential tool to assess performance. For pedagogical purposes the book includes several computational problems and exercices. To prevent students from getting stuck on exercises, detailed corrections are provided.

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Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python

About This Book:​

• Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes
• Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis
• Create a basic indoor routing application with geodjango

Who This Book Is For:​

If you are a student, teacher, programmer, geospatial or IT administrator, GIS analyst, researcher, or...

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Build and play your own computer games, from creative quizzes to perplexing puzzles, by coding them in the Python programming language!

Whether you're a seasoned programmer or a beginner hoping to learn Python, you'll find Coding Games in Python fun to read and easy to follow. Each chapter shows you how to construct a complete working game in simple numbered steps. Using freely available resources such as Pygame, Pygame Zero, and a downloadable pack of images and sounds, you can add animations, music, scrolling backgrounds, scenery, and other exciting professional touches.

After building the game, find out how to adapt it to create...

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Master how to build dynamic HTML5-ready SVG charts using Python and the pygal library

About This Book:​

• A practical guide that helps you break into the world of data visualization with Python
• Understand the fundamentals of building charts in Python
• Packed with easy-to-understand tutorials for developers who are new to Python or charting in Python

Who This Book Is For:​

If you are a Python novice or an experienced developer and want to explore data visualization libraries, then this is the book for you. No prior charting or graphics experience is...

DESCRIPTION:

Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction? Then this is the book for you. You’ll cut through the complexity of online documentation and discover how easily you can get up to speed with these Python libraries.

Ideal for data analysts and scientists in any field, this overview shows you how to use NumPy for numerical processing, including array indexing, math operations, and loading and saving data. You’ll learn how SciPy helps you work with advanced mathematical functions such as optimization, interpolation, integration, clustering, statistics, and other...

DESCRIPTION:

This is a book about doing things with Django admin. It takes the form of about forty questions and common tasks with Django admin.

This book serves as a reference when you are trying to do more with Django Admin, and as a tutorial to expand your knowledge and skill with Django.

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Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.

Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this.

This book is based...

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This textbook presents an introduction to generalized linear models, complete with real-world data sets and practice problems, making it applicable for both beginning and advanced students of applied statistics. Generalized linear models (GLMs) are powerful tools in applied statistics that extend the ideas of multiple linear regression and analysis of variance to include response variables that are not normally distributed. As such, GLMs can model a wide variety of data types including counts, proportions, and binary outcomes or positive quantities.

The book is designed with the student in mind, making it suitable for self-study or...

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Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools for data visualization and representation.

The book considers graphical displays of a single discrete variable, a single continuous variable, and then two or more of each of these. It includes displays and the R code for producing the displays for the dot chart, bar chart, pictographs, stemplot, boxplot, and variations on the...

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Master the programming skills you need to turn raw, unfiltered data into deep insights and get ready for a data science and analytics career with this definitive guide to R Programming for Beginners!​

Do you want to get started learning how to program, but don't know where to begin? Are you interested in moving beyond Excel sheets and learning one of the most powerful programming language used in cutting edge research such as machine learning?

If you answered yes to any of these questions, then this book might just be what you need.

R can be a royal pain in the neck sometimes. Even seasoned programmers and data analysts...

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Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications.

The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis...