Coffee Break Numpy

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Coffee Break Numpy
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Author : Lukas Rieger
language : en
Publisher:
Release Date : 2019-06-28
Coffee Break Numpy written by Lukas Rieger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-28 with categories.
Fear of missing out in data science? Coffee Break NumPy is a new step-by-step system to teach you how to learn Python's library for data science faster, smarter, and better. You simply solve practical Python NumPy puzzles as you enjoy your morning coffee. Educational research shows that practical low-stake puzzles and tests help you to learn faster, smarter, and better. Over 100,000 online Python students have already improved their coding and NumPy skills with the unique Finxter.com puzzle-based learning technique: "It has some real meat to the problems. Thank you so much for doing this project! I love it!" --David C. "Another great little Python book from Christian and his colleagues. As a practitioner in this field, I really appreciate the focus on real-world problems. I can see my coffee breaks will be full for some time to come!" --Chris C. As you work through Coffee Break NumPy, your NumPy expertise will grow--one coffee at a time. It's packed with 46 NumPy puzzles, 10 practical learning tips, 1 compressed cheat sheets, and 1 new way to measure your coding skills. You will train wildly important NumPy topics such as NumPy Arrays: creating, basic array arithmetic, one- and multi-dimensional Data Types: float, integer, mixed, access, conversion Shape and Reshape: manipulating, accessing, axis argument Broadcasting: element-wise operations Indexing and Advanced Indexing: filtering, Boolean indexing, list indexing Slicing: one-dimensional, multi-dimensional, NumPy-specifics As a bonus, you will track your individual Python coding skill level throughout the book. To get most out of this book, you already have basic Python skills. For example, you've read my book "Coffee Break Python" or similar introductory Python material. So how do you spend your Coffee Break? Python!
Coffee Break Python
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Author : Christian Mayer
language : en
Publisher:
Release Date : 2018-09-10
Coffee Break Python written by Christian Mayer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-10 with categories.
How to learn Python during your coffee break? Coffee Break Python is a new step-by-step system to teach you how to learn Python faster, smarter, and better. You do nothing but solving one practical Python puzzle as you enjoy your morning coffee. Why should you care about puzzle-based learning? Educational research shows that practical low-stake puzzles and tests help you to learn faster, smarter, and better. We used this for coding in Coffee Break Python and our academy Finxter.com. 13,000 online Python students have already improved their coding skills with our unique puzzle-based learning technique: "I very much enjoy your Finxter.com website because it has some real meat to the problems. Thank you so much for doing this project! I love it!" --David C. "Your site is awesome." --Victor A. "I found Finxter.com an excellent tool to brush up on my Python skills. I totally love the setup of playing against the questions - such a wonderful idea --Jesper R. Why should you read this book? As you work through Coffee Break Python, your Python expertise will grow--one coffee at a time. It's packed with 50 Python puzzles, 10 practical learning tips, 5 compressed cheat sheets, and 1 new way to measure your coding skills. You will train wildly important Python topics such as Arithmetic operations: integer & float division, and modular arithmetic; Language elements: branching, loops, keywords, and functions; Data structures: integer, float, string, list, set, dictionary, and graph; Sequence operators: indexing, concatenation, slicing, and built-in functions; Function *arguments: default *, arbitrary *, unpacking *, keyword *; Set operations: lambda, filter, map, and intersection functions; and Algorithms: recursion, Fibonacci, matrix search, bubble sort, quick sort, lexicographical sort, guess & check, binary search, and graph traversal. As a bonus, you will track your individual Python coding skill level throughout the book. Who should read this book? You are slightly beyond beginner-level in Python. For example, You have already experience with another programming language--it's time to tackle Python. You are a professional engineer and want to brush up your Python skills. You are a student and need to get better at Python for academic courses. So how do you spend your Coffee Break? Python!
Python One Liners
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Author : Christian Mayer
language : en
Publisher: No Starch Press
Release Date : 2020-05-12
Python One Liners written by Christian Mayer and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-12 with Computers categories.
Python programmers will improve their computer science skills with these useful one-liners. Python One-Liners will teach you how to read and write "one-liners": concise statements of useful functionality packed into a single line of code. You'll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert. The book's five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills. You'll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments. You'll also learn how to: • Leverage data structures to solve real-world problems, like using Boolean indexing to find cities with above-average pollution • Use NumPy basics such as array, shape, axis, type, broadcasting, advanced indexing, slicing, sorting, searching, aggregating, and statistics • Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning • Create more advanced regular expressions using grouping and named groups, negative lookaheads, escaped characters, whitespaces, character sets (and negative characters sets), and greedy/nongreedy operators • Understand a wide range of computer science topics, including anagrams, palindromes, supersets, permutations, factorials, prime numbers, Fibonacci numbers, obfuscation, searching, and algorithmic sorting By the end of the book, you'll know how to write Python at its most refined, and create concise, beautiful pieces of "Python art" in merely a single line.
The Big Book Of Small Python Projects
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Author : Al Sweigart
language : en
Publisher: No Starch Press
Release Date : 2021-06-25
The Big Book Of Small Python Projects written by Al Sweigart and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Computers categories.
Best-selling author Al Sweigart shows you how to easily build over 80 fun programs with minimal code and maximum creativity. If you’ve mastered basic Python syntax and you’re ready to start writing programs, you’ll find The Big Book of Small Python Projects both enlightening and fun. This collection of 81 Python projects will have you making digital art, games, animations, counting pro- grams, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches. These simple, text-based programs are 256 lines of code or less. And whether it’s a vintage screensaver, a snail-racing game, a clickbait headline generator, or animated strands of DNA, each project is designed to be self-contained so you can easily share it online. You’ll create: • Hangman, Blackjack, and other games to play against your friends or the computer • Simulations of a forest fire, a million dice rolls, and a Japanese abacus • Animations like a virtual fish tank, a rotating cube, and a bouncing DVD logo screensaver • A first-person 3D maze game • Encryption programs that use ciphers like ROT13 and Vigenère to conceal text If you’re tired of standard step-by-step tutorials, you’ll love the learn-by-doing approach of The Big Book of Small Python Projects. It’s proof that good things come in small programs!
Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Hands On Data Science And Python Machine Learning
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Author : Frank Kane
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-07-31
Hands On Data Science And Python Machine Learning written by Frank Kane and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-31 with Computers categories.
This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.
Coffee Break Python Slicing
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Author : Christian Mayer
language : en
Publisher:
Release Date : 2018-11-22
Coffee Break Python Slicing written by Christian Mayer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-22 with categories.
Do you still waste your time PASSIVELY reading Python books? Puzzle-based learning is an ACTIVE learning technique. With code puzzles, you will learn faster, smarter, and better. The Coffee Break Python book series teaches you Python in byte-sized code puzzles. You solve a code puzzle a day while you enjoy your morning coffee. It's that simple. What do others have to say? 21,000 online Python students have already improved their coding skills with our unique puzzle-based learning technique: "I very much enjoy your Finxter.com website because it has some real meat to the problems. Thank you so much for doing this project! I love it!" --David C. "Your site is awesome." --Victor A. "I found Finxter.com an excellent tool to brush up on my Python skills. I totally love the setup of playing against the questions - such a wonderful idea --Jesper R. Why should you read this book? Coffee Break Python Slicing is all about growing your Python expertise--one coffee at a time. The focus lies on the important slicing technique to access consecutive data ranges. Understanding slicing thoroughly is crucial for your success as a Python developer. This book teaches you everything you need to know about slicing in Python. As a bonus, you will track your individual Python coding skill level throughout the book. Who should read this book? You are slightly beyond beginner-level in Python. For example, You have already experience with another programming language--it's time to tackle Python. You are a professional engineer and want to brush up your Python skills. You are a student and need to get better at Python for academic courses. You have read the first book of our Coffee Break Python series. So how do you spend your Coffee Break? Python!
Effective Computation In Physics
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Author : Anthony Scopatz
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-06-25
Effective Computation In Physics written by Anthony Scopatz and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-25 with Science categories.
More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results. In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures
Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.