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Found inside – Page iWho This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students Master the essential skills needed to recognize and solve complex problems with machine learning and deep 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 insideThis hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. Found insideLet Python handle the grunt work while you focus on the math. Found insideAuthor Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. The book will take you on a journey through the evolution of data analysis explaining each step in the process in a very simple and easy to understand manner. 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. 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. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. Found insideThis book constitutes the refereed proceedings of 3 workshops co-located with International Conference for High Performance Computing, Networking, Storage, and Analysis, SC19, held in Denver, CO, USA, in November 2019. Found inside – Page iAfter 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 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 ... Get to grips with the basics of JupyterLab and its web interface with the help of this quick start guide Key Features Manage JupyterLab kernels, code consoles, and terminals, and share your work over the cloud Organize your data solutions ... Found inside – Page 1Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Found inside – Page iThis book provides the essential foundations of both linear and nonlinear analysis necessary for understanding and working in twenty-first century applied and computational mathematics. Found insideIn The Perfect Bet, mathematician and award-winning writer Adam Kucharski tells the astonishing story of how the experts have succeeded, revolutionizing mathematics and science in the process. The house can seem unbeatable. Found inside11 Python standard libraries and Conda Python libraries and python packages play ... anaconda $ conda update -c conda-forge jupyterlab $ conda update --all ... This powerful book: • examines the reality of design in practice • shares tools and resources to guide practice • analyses design within complex systems • discusses the influence of open resources on design • includes design ... This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and ... Found inside – Page iWritten by experienced hedge fund manager Andreas Clenow, this book provides a comprehensive insight into the strategies behind the booming trend following futures industry from the perspective of a market participant. Presents case studies and instructions on how to solve data analysis problems using Python. Found inside – Page iThis book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Found insideGet to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery About This Book Get comfortable using pandas and Python as an effective data exploration and analysis tool Explore ... Found insidePython Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. After reading and using this book, you will be proficient in writing clean Python code and successfully apply these principles to your own Python projects. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Found insideLeverage the computational power of Python with more than 60 recipes that arm you with the required skills to make informed business decisions About This Book Want to minimize risk and optimize profits of your business? Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists. 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 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 will be a handy guide to quickly learn pandas and understand how it can empower you in the exciting world of data manipulation, analysis, and data science. 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 ... This book consists of ten chapters which outline a wide range of technologies from first-principle calculations to continuum mechanics, with applications to materials design and development. Found inside – Page iThis book draws upon author Moshe Zadka's years of Dev Ops experience and focuses on the parts of Python, and the Python ecosystem, that are relevant for DevOps engineers. This is a highly practical book, where every aspect is explained, all source code shown and no holds barred. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. 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 ... This book is neither a textbook in numerical methods, a comprehensive introductory book to Julia programming, a textbook on numerical optimization, a complete manual of optimization solvers, nor an introductory book to computational science ... What this book aims to do... This book is written with one goal in mind - to help beginners overcome their initial obstacles to learning Data Visualization using Python. A lot of times, newbies tend to feel intimidated by coding and data. 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 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 ... I have found that while learning how the various widgets work in wxPython is valuable, it is even better to learn by creating a simple application that does something useful.In this book, you will be creating the following applications: - A ... Found insideWhat you will learn Configure a local instance of PySpark in a virtual environment Install and configure Jupyter in local and multi-node environments Create DataFrames from JSON and a dictionary using pyspark.sql Explore regression and ... 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 ... 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 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 ... "--Thomas M. Malaby, University of Wisconsin-Milwaukee "This is a revelatory ethnographic look at the origins and evolution of the free and open source software subculture. 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