Found inside – Page iWhat You'll Learn Understand the core concepts of data analysis and the Python ecosystem Go in depth with pandas for reading, writing, and processing data Use tools and techniques for data visualization and image analysis Examine popular ... Found inside – Page 30I'll show you a keyboard shortcut to change the cell mode in Table 2-3. After changing an empty cell into a Markdown cell, type in the following text, ... Found inside – Page i8 Improved functionality and performance 9 Improved color conversion API and RGBA support 9 Improved image support 9 Faster text rendering 9 Change in the ... Your one-stop guide to building an efficient data science pipeline using JupyterAbout This Book* Get the most out of your Jupyter notebook to complete the trickiest of tasks in Data Science* Learn all the tasks in the data science pipeline ... Found insideWhat you will learn Explore important Python libraries and learn to install Anaconda distribution Understand the basics of NumPy Produce informative and useful visualizations for analyzing data Perform common statistical calculations Build ... Found inside – Page 1This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. What you will learn See how quantum computing works, delve into the math behind it, what makes it different, and why it is so powerful with this quantum computing textbook Discover the complex, mind-bending mechanics that underpin quantum ... "This book by Lisa Tauxe and others is a marvelous tool for education and research in Paleomagnetism. Found insideThis book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications. Found inside – Page iThis open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. Found insideWhat you will learn Get up and running with the Jupyter ecosystem and some example datasets Learn about key machine learning concepts like SVM, KNN classifiers, and Random Forests Plan a machine learning classification strategy and train ... Found insideWith 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 ... Found insideBecome 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 ... Found insideThis hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch. First time paperback of successful physics monograph. Copyright © Libri GmbH. All rights reserved. Found insideTowards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book. Style and approach This comprehensive practical guide will teach you how to work with the Jupyter Notebook system. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain ... Found insideThrough this book, you'll learn Jupyter Notebooks, the technology used in academic and commercial circles with in-line code running support. Found insideYou can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub. "This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience"-- An introduction to Prolog programming for artificial intelligence covering both basic and advanced AI material. A unique advantage to this work is the combination of AI, Prolog and Logic. Found insideGet 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 ... Found insideThis book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more. Found insideToday ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Found insideThis book is about making machine learning models and their decisions interpretable. But it doesn't stop there! In this volume, you'll find detailed guides on the most important multimedia applications on Linux today: the Kdenlive video editor and the Qtractor digital audio workstation. blogdown: Creating Websites with R Markdown provides a practical guide for creating websites using the blogdown package in R. In this book, we show you how to use dynamic R Markdown documents to build static websites featuring R code (or ... Found insideWe can also add rich content in the Jupyter Notebook using markup language in the cells and change the cell type using the “Cell” menu to markdown. What you will learn Use Python to read and transform data into different formats Generate basic statistics and metrics using data on disk Work with computing tasks distributed over a cluster Convert data from various sources into storage or ... What you will learn Understand how to install and manage Anaconda Read, sort, and map data using NumPy and pandas Find out how to create and slice data arrays using NumPy Discover how to subset your DataFrames using pandas Handle missing ... Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists. Found insideF. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer ... Found insideWhat you will learn Discover how you can assemble and clean your very own datasets Develop a tailored machine learning classification strategy Build, train and enhance your own models to solve unique problems Work with production-ready ... Data Science Projects with Python will help you get comfortable with using the Python environment for data science. This book will start you on your journey to mastering topics within machine learning. Get started solving problems with the Python programming language!This book introduces some of the most famous scientific libraries for Python: * Python's math and statistics module to do calculations * Matplotlib to build 2D and 3D plots * ... Found inside – Page 640Used with permission of Project Jupyter To start Jupyter Notebook, ... within which you will create and edit your notebooks, as shown in FIGURE 16.12. The book uses free software and code that can be run on any platform. Found inside – Page 1Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Deep Learning with PyTorch teaches you to create deep learning and neural network systems with PyTorch. This practical book gets you to work right away building a tumor image classifier from scratch. How seeing turns into showing, how empirical observations turn into explanation and evidence. How to produce and consume evidence presentations. Found insideKey Features: Convert static ggplot2 graphics to an interactive web-based form Link, animate, and arrange multiple plots in standalone HTML from R Embed, modify, and respond to plotly graphics in a shiny app Learn best practices for ... Found inside – Page iThis book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Presents case studies and instructions on how to solve data analysis problems using Python. Found insideAfter introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. Found inside8 Changes to the default style 8 Color cycle 9 Saving the notebook ... 12 Faster text rendering 12 Change in the default animation codec 12 Changes in ... Found insideWhat you will learn Install and run the Jupyter Notebook system on your machine Implement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook Use interactive widgets to manipulate and visualize data in ... Found insideIn this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. This anthology of essays from the inventor of literate programming includes Knuth's early papers on related topics such as structured programming, as well as the Computer Journal article that launched literate programming itself. Found insideIn 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 ... Are you ready to join them? This book helps you use and understand basic SAS software, including SAS® Enterprise Guide®, SAS® Add-In for Microsoft® Office, and SAS® Web Report Studio. 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