Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Ipython Notebook Essentials
Download Ipython Notebook Essentials full books in PDF, epub, and Kindle. Read online Ipython Notebook Essentials ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis IPython Notebook Essentials by : L. Felipe Martins
Download or read book IPython Notebook Essentials written by L. Felipe Martins and published by Packt Publishing Ltd. This book was released on 2014-11-21 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.
Book Synopsis Python Data Science Handbook by : Jake VanderPlas
Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. 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. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Book Synopsis Python Data Science Essentials by : Alberto Boschetti
Download or read book Python Data Science Essentials written by Alberto Boschetti and published by Packt Publishing Ltd. This book was released on 2016-10-28 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
Book Synopsis Python for Data Analysis by : Wes McKinney
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Book Synopsis Deep Learning with Python by : Francois Chollet
Download or read book Deep Learning with Python written by Francois Chollet and published by Simon and Schuster. This book was released on 2017-11-30 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary 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 François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book 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 François 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 Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance
Book Synopsis Learning IPython for Interactive Computing and Data Visualization by : Cyrille Rossant
Download or read book Learning IPython for Interactive Computing and Data Visualization written by Cyrille Rossant and published by Packt Publishing Ltd. This book was released on 2015-10-21 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with Python for data analysis and numerical computing in the Jupyter notebook About This Book Learn the basics of Python in the Jupyter Notebook Analyze and visualize data with pandas, NumPy, matplotlib, and seaborn Perform highly-efficient numerical computations with Numba, Cython, and ipyparallel Who This Book Is For This book targets students, teachers, researchers, engineers, analysts, journalists, hobbyists, and all data enthusiasts who are interested in analyzing and visualizing real-world datasets. If you are new to programming and data analysis, this book is exactly for you. If you're already familiar with another language or analysis software, you will also appreciate this introduction to the Python data analysis platform. Finally, there are more technical topics for advanced readers. No prior experience is required; this book contains everything you need to know. What You Will Learn Install Anaconda and code in Python in the Jupyter Notebook Load and explore datasets interactively Perform complex data manipulations effectively with pandas Create engaging data visualizations with matplotlib and seaborn Simulate mathematical models with NumPy Visualize and process images interactively in the Jupyter Notebook with scikit-image Accelerate your code with Numba, Cython, and IPython.parallel Extend the Notebook interface with HTML, JavaScript, and D3 In Detail Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors. This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data. Style and approach This is a hands-on beginner-friendly guide to analyze and visualize data on real-world examples with Python and the Jupyter Notebook.
Download or read book R Markdown written by Yihui Xie and published by CRC Press. This book was released on 2018-07-27 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages. In this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ioslides/Slidy/Beamer/PowerPoint presentations Extensions and applications: Dashboards, Tufte handouts, xaringan/reveal.js presentations, websites, books, journal articles, and interactive tutorials Advanced topics: Parameterized reports, HTML widgets, document templates, custom output formats, and Shiny documents. Yihui Xie is a software engineer at RStudio. He has authored and co-authored several R packages, including knitr, rmarkdown, bookdown, blogdown, shiny, xaringan, and animation. He has published three other books, Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, and blogdown: Creating Websites with R Markdown. J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown ecosystem including rmarkdown, flexdashboard, learnr, and radix. Garrett Grolemund is the co-author of R for Data Science and author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as an advocate who trains engineers to do data science with R and the Tidyverse.
Book Synopsis Jupyter Notebook 101 by : Michael Driscoll
Download or read book Jupyter Notebook 101 written by Michael Driscoll and published by R. R. Bowker. This book was released on 2018-10-24 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Jupyter Notebook 101 will teach you all you need to know to create and use Notebooks effectively. You can use Jupyter Notebook to help you learn to code, create presentations, and make beautiful documentation.The Jupyter Notebook is used by the scientific community to demonstrate research in an easy-to-replicate manner.You will learn the following in Jupyter Notebook 101: - How to create and edit Notebooks - How to add styling, images, graphs, etc - How to configure Notebooks - How to export your Notebooks to other formats - Notebook extensions - Notebook widgets - Using Notebooks for presentations - Debugging Notebooks - Running tests against and inside Notebooks - An intro to JupyterLab
Book Synopsis Interactive Applications Using Matplotlib by : Benjamin V. Root
Download or read book Interactive Applications Using Matplotlib written by Benjamin V. Root and published by Packt Publishing Ltd. This book was released on 2015-03-24 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.
Download or read book Python for DevOps written by Noah Gift and published by O'Reilly Media. This book was released on 2019-12-12 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project
Book Synopsis Python and Matplotlib Essentials for Scientists and Engineers by : Matt A Wood
Download or read book Python and Matplotlib Essentials for Scientists and Engineers written by Matt A Wood and published by Morgan & Claypool Publishers. This book was released on 2015-06-01 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the core features of the Python programming language and Matplotlib plotting routings for scientists and engineers (or students of either discipline) who want to use PythonTM to analyse data, simulate physical processes, and render publication-quality plots. No previous programming experience is needed before reading the first page. Readers will learn the core features of the Python programming language in under a day. They will be able to immediately use Python to implement codes that solve their own problems and make beautiful plots and animations. Python code is extremely fast to prototype, allowing users to achieve results quickly and accurately. The examples within the book are available for download at http://pythonessentials.com. Python and Matplotlib Essentials for Scientists and Engineers is accessible for motivated high-school students, but will likely be most useful for undergraduate and graduate students as well as working professionals who have some background with the basic mathematical concepts. This book is intended for technical people who want to get things done.
Book Synopsis Network Programming and Automation Essentials by : Claus Topke
Download or read book Network Programming and Automation Essentials written by Claus Topke and published by Packt Publishing Ltd. This book was released on 2023-04-07 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the power of automation by mastering network programming fundamentals using Python and Go best practices Purchase of the print or Kindle book includes a free PDF eBook Key Features Understand the fundamentals of network programming and automation Learn tips and tricks to transition from traditional networking to automated networks Solve everyday problems with automation frameworks in Python and Go Book Description Network programming and automation, unlike traditional networking, is a modern-day skill that helps in configuring, managing, and operating networks and network devices. This book will guide you with important information, helping you set up and start working with network programming and automation. With Network Programming and Automation Essentials, you'll learn the basics of networking in brief. You'll explore the network programming and automation ecosystem, learn about the leading programmable interfaces, and go through the protocols, tools, techniques, and technologies associated with network programming. You'll also master network automation using Python and Go with hands-on labs and real network emulation in this comprehensive guide. By the end of this book, you'll be well equipped to program and automate networks efficiently. What you will learn Understand the foundation of network programming Explore software-defined networks and related families Recognize the differences between Go and Python through comparison Leverage the best practices of Go and Python Create your own network automation testing framework using network emulation Acquire skills in using automation frameworks and strategies for automation Who this book is for This book is for network architects, network engineers, and software professionals looking to integrate programming into networks. Network engineers following traditional techniques can use this book to transition into modern-day network automation and programming. Familiarity with networking concepts is a prerequisite.
Book Synopsis IPython Interactive Computing and Visualization Cookbook by : Cyrille Rossant
Download or read book IPython Interactive Computing and Visualization Cookbook written by Cyrille Rossant and published by Packt Publishing Ltd. This book was released on 2014-09-25 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
Book Synopsis Python for Signal Processing by : José Unpingco
Download or read book Python for Signal Processing written by José Unpingco and published by Springer Science & Business Media. This book was released on 2013-10-04 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.
Book Synopsis Mastering pandas for Finance by : Michael Heydt
Download or read book Mastering pandas for Finance written by Michael Heydt and published by Packt Publishing Ltd. This book was released on 2015-05-25 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.
Book Synopsis NumPy Essentials by : Leo (Liang-Huan) Chin
Download or read book NumPy Essentials written by Leo (Liang-Huan) Chin and published by Packt Publishing Ltd. This book was released on 2016-04-28 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Boost your scientific and analytic capabilities in no time at all by discovering how to build real-world applications with NumPy About This Book Optimize your Python scripts with powerful NumPy modules Explore the vast opportunities to build outstanding scientific/ analytical modules by yourself Packed with rich examples to help you master NumPy arrays and universal functions Who This Book Is For If you are an experienced Python developer who intends to drive your numerical and scientific applications with NumPy, this book is for you. Prior experience or knowledge of working with the Python language is required. What You Will Learn Manipulate the key attributes and universal functions of NumPy Utilize matrix and mathematical computation using linear algebra modules Implement regression and curve fitting for models Perform time frequency / spectral density analysis using the Fourier Transform modules Collate with the distutils and setuptools modules used by other Python libraries Establish Cython with NumPy arrays Write extension modules for NumPy code using the C API Build sophisticated data structures using NumPy array with libraries such as Panda and Scikits In Detail In today's world of science and technology, it's all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy gives you both the speed and high productivity you need. This book will walk you through NumPy using clear, step-by-step examples and just the right amount of theory. We will guide you through wider applications of NumPy in scientific computing and will then focus on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier Transform; solving linear systems of equations, interpolation, extrapolation, regression, and curve fitting; and evaluating integrals and derivatives. We will also introduce you to using Cython with NumPy arrays and writing extension modules for NumPy code using the C API. This book will give you exposure to the vast NumPy library and help you build efficient, high-speed programs using a wide range of mathematical features. Style and approach This quick guide will help you get to grips with the nitty-gritties of NumPy using with practical programming examples. Each topic is explained in both theoretical and practical ways with hands-on examples providing you efficient way of learning and adequate knowledge to support your professional work.
Book Synopsis Essentials of Data Science and Analytics by : Amar Sahay
Download or read book Essentials of Data Science and Analytics written by Amar Sahay and published by Business Expert Press. This book was released on 2021-07-06 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science and analytics have emerged as the most desired fields in driving business decisions. Using the techniques and methods of data science, decision makers can uncover hidden patterns in their data, develop algorithms and models that help improve processes and make key business decisions. Data science is a data driven decision making approach that uses several different areas and disciplines with a purpose of extracting insights and knowledge from structured and unstructured data. The algorithms and models of data science along with machine learning and predictive modeling are widely used in solving business problems and predicting future outcomes. This book combines the key concepts of data science and analytics to help you gain a practical understanding of these fields. The four different sections of the book are divided into chapters that explain the core of data science. Given the booming interest in data science, this book is timely and informative.
