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Numpy Beginners Guide
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Book Synopsis NumPy Beginner's Guide (Second Edition) by : Ivan Idris
Download or read book NumPy Beginner's Guide (Second Edition) written by Ivan Idris and published by Packt Publishing Ltd. This book was released on 2013-04-25 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is written in beginner’s guide style with each aspect of NumPy demonstrated with real world examples and required screenshots.If you are a programmer, scientist, or engineer who has basic Python knowledge and would like to be able to do numerical computations with Python, this book is for you. No prior knowledge of NumPy is required.
Book Synopsis NumPy: Beginner's Guide by : Ivan Idris
Download or read book NumPy: Beginner's Guide written by Ivan Idris and published by Packt Publishing Ltd. This book was released on 2015-06-24 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 will give you both speed and high productivity. This book will walk you through NumPy with clear, step-by-step examples and just the right amount of theory. The book focuses 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, finding the inverse of a matrix, and determining eigenvalues, among many others. This book is a one-stop solution to knowing the ins and outs of the vast NumPy library, empowering you to use its wide range of mathematical features to build efficient, high-speed programs.
Book Synopsis Learning NumPy Array by : Ivan Idris
Download or read book Learning NumPy Array written by Ivan Idris and published by Packt Publishing Ltd. This book was released on 2014-06-13 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step guide, packed with examples of practical numerical analysis that will give you a comprehensive, but concise overview of NumPy. This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python.
Download or read book Guide to NumPy written by Travis Oliphant and published by CreateSpace. This book was released on 2015-09-15 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second edition of Travis Oliphant's A Guide to NumPy originally published electronically in 2006. It is designed to be a reference that can be used by practitioners who are familiar with Python but want to learn more about NumPy and related tools. In this updated edition, new perspectives are shared as well as descriptions of new distributed processing tools in the ecosystem, and how Numba can be used to compile code using NumPy arrays. Travis Oliphant is the co-founder and CEO of Continuum Analytics. Continuum Analytics develops Anaconda, the leading modern open source analytics platform powered by Python. Travis, who is a passionate advocate of open source technology, has a Ph.D. from Mayo Clinic and B.S. and M.S. degrees in Mathematics and Electrical Engineering from Brigham Young University. Since 1997, he has worked extensively with Python for computational and data science. He was the primary creator of the NumPy package and founding contributor to the SciPy package. He was also a co-founder and past board member of NumFOCUS, a non-profit for reproducible and accessible science that supports the PyData stack. He also served on the board of the Python Software Foundation.
Download or read book NumPy written by Ivan Idris and published by . This book was released on 2015 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build efficient, high-speed programs using the high-performance NumPy mathematical library 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 will give you both speed and high productivity. This book will walk you through NumPy with clear, step-by-step examples and just the right amount of theory. The book focuses 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, finding the inverse of a matrix, and determining eigenvalues, among many others. This book is a one-stop solution to knowing the ins and outs of the vast NumPy library, empowering you to use its wide range of mathematical features to build efficient, high-speed programs. What You Will Learn Install NumPy, matplotlib, SciPy, and IPython on various operating systems Use NumPy array objects to perform array operations Familiarize yourself with commonly used NumPy functions Use NumPy matrices for matrix algebra Work with the NumPy modules to perform various algebraic operations Test NumPy code with the numpy.testing module Plot simple plots, subplots, histograms, and more with matplotlib Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
Book Synopsis NumPy Beginner's Guide by : Ivan Idris
Download or read book NumPy Beginner's Guide written by Ivan Idris and published by . This book was released on 2013 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Python for Data Analysis by : Brady Ellison
Download or read book Python for Data Analysis written by Brady Ellison and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Ready to learn Data Science through Python language? Python for Data Analysis is a step-by-step guide for beginners and dabblers-alike. This book is designed to offer working knowledge of Python and data science and some of the tools required to apply that knowledge. It’s possible that you have little experience with or knowledge of data analysis and are interested in it. You might have some experience in coding. You may have worked with data before and want to use Python. We have made this book in a way that will be helpful to all these groups and more besides in varying ways. This can serve as an introduction to the most current tools and functions of those tools used by data scientists. In this book You will learn: Data Science/Analysis and its applications IPython and Jupyter - an introduction to the basic tools and how to navigate and use them. You will also learn about its importance in a data scientist’s ecosystem. Pandas - a powerful data management Python library that lets you do interesting things with data. You will learn all the basics you need to get started. NumPy - a powerful numerical library for Python. You will learn more about its advantages. Get your copy now
Download or read book NumPy 1.5 written by Ivan Idris and published by Packt Pub Limited. This book was released on 2011 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is written in beginner's guide style with each aspect of NumPy demonstrated by real world examples. There is appropriate explained code with the required screenshots thrown in for the novice. This book is for the programmer, scientist or engineer, who has basic Python knowledge and would like to be able to do numerical computations with Python.
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 743 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
Download or read book Learning Python written by Samuel Hack and published by Independently Published. This book was released on 2019-08 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★★ Buy the Paperback Version of this Book and get the Kindle Book Version for FREE ★★ Are you looking to learn more about the world of coding and programming but you are worried that it is going to be too hard and too complicated to get started? Have you been interested in learning how to code but worry that it is too hard and that you won't be able to learn all of the different parts that come together to make a program work? Do you have a great idea for an app or a program that you want to create but you don't know how to make it all work and how to put it together? There are a lot of reasons to learn a new coding language but no matter what reason is behind your motivation, the Python coding language is going to be the platform that you need to make it all happen. This guidebook is going to spend some time looking into the Python coding language, and all of the different things that you are able to do with it. Inside this guidebook, we are going to explore a lot of the different parts of the Python code and how you can put it all together while learning how to code! Some of the topics that we will discuss inside include: What is Python and why would I want to learn how to work with it? The basics of the Python code and how to get started writing some of our own What it means that Python is an OOP language and how that is going to make a difference in my coding How to write some loops and conditional statements in the Python language What is an exception and how to handle the automatic exceptions in this code while writing some of your own How to work with an inheritance to save some room and make code writing a bit easier How to write some of your own regular expressions and why they are so important to your goals in code writing with Python A look at some of the best Python libraries including Matplotlib and Scikit-Learn and what you are able to do with them when you are working on your codes There is just so much that you will be able to do when you decide to work with the Python coding language. Even if you have never worked with any kind of coding language in the past. Python is definitely going to make things easy to start, and you will be writing some of your own codes in no time. When you are ready to get started with Python and writing some of your own Python codes, even with machine learning in the process make sure to check out this guidebook to help you get started. Scroll Up and Click the "Buy now" button!
Book Synopsis Python Machine Learning for Beginners by : Ai Publishing
Download or read book Python Machine Learning for Beginners written by Ai Publishing and published by . This book was released on 2020-10-23 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Machine Learning for BeginnersMachine Learning (ML) and Artificial Intelligence (AI) are here to stay. Yes, that's right. Based on a significant amount of data and evidence, it's obvious that ML and AI are here to stay.Consider any industry today. The practical applications of ML are really driving business results. Whether it's healthcare, e-commerce, government, transportation, social media sites, financial services, manufacturing, oil and gas, marketing and salesYou name it. The list goes on. There's no doubt that ML is going to play a decisive role in every domain in the future.But what does a Machine Learning professional do?A Machine Learning specialist develops intelligent algorithms that learn from data and also adapt to the data quickly. Then, these high-end algorithms make accurate predictions. Python Machine Learning for Beginners presents you with a hands-on approach to learn ML fast.How Is This Book Different?AI Publishing strongly believes in learning by doing methodology. With this in mind, we have crafted this book with care. You will find that the emphasis on the theoretical aspects of machine learning is equal to the emphasis on the practical aspects of the subject matter.You'll learn about data analysis and visualization in great detail in the first half of the book. Then, in the second half, you'll learn about machine learning and statistical models for data science.Each chapter presents you with the theoretical framework behind the different data science and machine learning techniques, and practical examples illustrate the working of these techniques.When you buy this book, your learning journey becomes so much easier. The reason is you get instant access to all the related learning material presented with this book--references, PDFs, Python codes, and exercises--on the publisher's website. All this material is available to you at no extra cost. You can download the ML datasets used in this book at runtime, or you can access them via the Resources/Datasets folder.You'll also find the short course on Python programming in the second chapter immensely useful, especially if you are new to Python. Since this book gives you access to all the Python codes and datasets, you only need access to a computer with the internet to get started. The topics covered include: Introduction and Environment Setup Python Crash Course Python NumPy Library for Data Analysis Introduction to Pandas Library for Data Analysis Data Visualization via Matplotlib, Seaborn, and Pandas Libraries Solving Regression Problems in ML Using Sklearn Library Solving Classification Problems in ML Using Sklearn Library Data Clustering with ML Using Sklearn Library Deep Learning with Python TensorFlow 2.0 Dimensionality Reduction with PCA and LDA Using Sklearn Click the BUY NOW button to start your Machine Learning journey.
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
Download or read book SciPy and NumPy written by Eli Bressert and published by "O'Reilly Media, Inc.". This book was released on 2012 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Optimizing and boosting your Python programming"--Cover.
Book Synopsis Python Machine Learning by : Lilly Trinity
Download or read book Python Machine Learning written by Lilly Trinity and published by . This book was released on 2020-01-03 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python is high-level programming, general- purpose language that is increasingly used in data science and the design of machine learning algorithms. This book gives a quick introduction to Python and its libraries such as numpy, scipy, pandas, matplotlib, and how it can be used to develop machine learning algorithms that solve real problems. In this book, you will discover information and advices on: What machine learning is Libraries and Packages used to perform various machine learning tasks Applications of machine learning How to install python on your system Data pre-processing techniques Techniques and Algorithm used in machine learning And more... This book begins with an introduction to machine learning and the Python language and explains how to configure Python and its packages. It also covers all important concepts such as exploratory data analysis, data pre-processing, feature extraction, data visualization, and grouping, classification, regression, and performance evaluation of the model. This book also features several projects that teach techniques and features such as sorting news topics, detecting junk e-mail, forecasting online ad clicks, stock price forecasting, and several other machine learning algorithms. We have written this book for professionals who are willing to learn the basics of Python and develop applications and software by making use of the machine learning techniques such as grouping, recommendation, and classification. In this book, you will be taught how to solve data problems and implement your solutions using the powerful but simple Python programming language and its packages. After reading this book, you will get a broad overview of the machine learning environment and best practices for machine learning techniques.
Download or read book NumPy Cookbook written by Ivan Idris and published by Packt Publishing Ltd. This book was released on 2012-10-25 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in Cookbook style, the code examples will take your Numpy skills to the next level. This book will take Python developers with basic Numpy skills to the next level through some practical recipes.
Book Synopsis Numerical Python by : Robert Johansson
Download or read book Numerical Python written by Robert Johansson and published by Apress. This book was released on 2018-12-24 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. 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-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning. What You'll Learn Work with vectors and matrices using NumPy Plot and visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Review statistical modeling and machine learning with statsmodels and scikit-learn Optimize Python code using Numba and Cython Who This Book Is For Developers who want to understand how to use Python and its related ecosystem for numerical computing.
Book Synopsis Python Data Science by : Jessica Rizzo
Download or read book Python Data Science written by Jessica Rizzo and published by . This book was released on 2019-08-25 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're tired of licensing third-party software for data analysis, Python Data Science will help you do it for yourself! Recently, more and more companies are learning that they need to make DATA-DRIVEN decisions. And with big data and data science on the rise, we now have more data than we know what to do with. In fact, without a doubt, you have already experienced data science in one way or another. Obviously, you are interacting with data science products every time you search for information on the web by using search engines such as Google, or asking for directions with your mobile phone. Data science is the science and technology focused on collecting raw data and processing it in an effective manner. It is the combination of concepts and methods that make it possible to give meaning and understandability to huge volumes of data. Data science has been the force behind resolving some of our most common daily tasks for several years. In nearly all of our daily work, we directly or indirectly work on storing and exchanging data. With the rapid development of technology, the need to store data effectively is also increasing. That's why it needs to be handled properly. Basically, data science unearths the hidden insights of raw-data and uses them for productive output. Python is often used in data science today because it is a mature programming language that has excellent properties for newbie programmers. Some of the most remarkable of these properties are its easy to read code, suppression of non-mandatory delimiters, dynamic typing, and dynamic memory usage. Python is an interpreted language, and it can be executed in the Python console without any need to compile to machine language. "Python Data Science" teaches a complete course of data science, including key topics like data integration, data mining, python etc. We will explore NumPy for numerical data, Pandas for data analysis, IPython, Scikit-learn and Tensorflow for machine learning and business. Each of the chapters in this book is devoted to one of the most interesting aspects of data analysis and processing. The following are some of the major topics covered in Python Data Science: Understanding Data Science Getting Started with Python for Data Scientists Descriptive statistics Data Analysis and Libraries NumPy Arrays and Vectorized Computation Data Analysis with Pandas Data Visualization Data Mining Classifying with Scikit-learn Estimators Giving Computers the Ability to Learn from Data Training Machine Learning Algorithms The Python ecosystem for data science discussed within Python Data Science includes SciPy, NumPy, Matplotlib, Pandas, and Scikit-learn, which provides all of the data science algorithms. Data processing and analysis is one of the hottest areas of IT, where developers who can handle projects of any level, from social networks to trained systems, are constantly required. We hope this book will be the starting point for your journey into the fascinating world of Data Science. To get started on your Python adventure, just scroll back up and click the 'Buy' button.
