Coffee Break Numpy
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| Author | : Lukas Rieger |
| Publisher | : |
| Total Pages | : 219 |
| Release | : 2019-06-28 |
| Genre | : |
| ISBN | : 9781076932617 |
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!
| Author | : Christian Mayer |
| Publisher | : |
| Total Pages | : 193 |
| Release | : 2018-09-10 |
| Genre | : |
| ISBN | : 9781719846585 |
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!
| Author | : Christian Mayer |
| Publisher | : No Starch Press |
| Total Pages | : 217 |
| Release | : 2020-05-12 |
| Genre | : Computers |
| ISBN | : 1718500513 |
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.
| Author | : John C. Shovic |
| Publisher | : John Wiley & Sons |
| Total Pages | : 704 |
| Release | : 2019-05-07 |
| Genre | : Computers |
| ISBN | : 1119557593 |
Your one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. Covers the basics of the language Explains its syntax through application in high-profile industries Shows how Python can be applied to projects in enterprise Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox.
| Author | : Lukas Rieger |
| Publisher | : |
| Total Pages | : 295 |
| Release | : 2019-08 |
| Genre | : |
| ISBN | : 9781086596465 |
This book is the chess grandmaster way of learning Python. It offers you 127 unique and brand-new Python puzzles. Every puzzle points to gaps in your knowledge, challenges you to guess a solution, and then explains potential solutions, in an easy-to-understand manner: ~~~ # Here's one example puzzle: my_list = [1, 1, 1, 1] my_list[1::2] = [2, 3] print(my_list) # What's the output of this code snippet? ~~~ An easy, fun, and effective way of learning Python -- day after day -- in your COFFEE BREAK PYTHON! Here's what research says about puzzle-based learning: "Students who were quizzed after studying a short text could recall significantly more information than students who were asked to reread it" -- Karpicke, 2007, Elsevier Journal of Memory and Language Practice testing is scientifically proven to generate up to 44% better learning retention and efficiency. Simply put: quizzes and puzzles work! More than 100,000 Finxters and thousands of "Coffee Break Python" book customers have already successfully improved their skills with code puzzles. Learning does not happen in a linear and orderly manner. It's a probabilistic, chaotic, and iterative process of creating knowledge gaps in your brain -- and filling them with just the right information you need. That's the premise of the "Coffee Break Python" textbook series. What will you get out of the book? Improve your level of deep Python code understanding. Surprise your peers with your newly acquired code speed reading skills. Enjoy the small daily doses of intellectual challenges. A Finxter once called it "Sudoku for coders"! ;) Improve your brain's working memory by hammering down the most important concepts. Learn all the basic Python syntax elements. Discover your own skill level by tracking your puzzle-solving performance. Compare your skill level against other coders: are you a grandmaster of code? Enjoy the fun of rushing over Python -- from "hello world" to "recursive Quicksort". Get the best of all Finxter Python cheat sheets to revive 80% of the Python features in 20% of the time. Get your dream job and rock future code interviews! And take one step forward mastering the most popular programming language ON THE PLANET!
| Author | : Chris Albon |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 285 |
| Release | : 2018-03-09 |
| Genre | : Computers |
| ISBN | : 1491989335 |
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models
| Author | : Joel Grus |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 336 |
| Release | : 2015-04-14 |
| Genre | : Computers |
| ISBN | : 1491904399 |
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
| Author | : Dan Bader |
| Publisher | : Dan Bader |
| Total Pages | : 302 |
| Release | : 2017 |
| Genre | : Computers |
| ISBN | : 9781775093305 |
"I don't even feel like I've scratched the surface of what I can do with Python" With Python Tricks: The Book you'll discover Python's best practices and the power of beautiful & Pythonic code with simple examples and a step-by-step narrative. You'll get one step closer to mastering Python, so you can write beautiful and idiomatic code that comes to you naturally. Learning the ins and outs of Python is difficult-and with this book you'll be able to focus on the practical skills that really matter. Discover the "hidden gold" in Python's standard library and start writing clean and Pythonic code today. Who Should Read This Book: If you're wondering which lesser known parts in Python you should know about, you'll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers' minds in your next code review. If you've got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2. If you've worked with other programming languages and you want to get up to speed with Python, you'll pick up the idioms and practical tips you need to become a confident and effective Pythonista. If you want to make Python your own and learn how to write clean and Pythonic code, you'll discover best practices and little-known tricks to round out your knowledge. What Python Developers Say About The Book: "I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." - Mariatta Wijaya, Python Core Developer "This book makes you write better Python code!" - Bob Belderbos, Software Developer at Oracle "Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." - Ben Felder, Pythonista "It's like having a seasoned tutor explaining, well, tricks!" - Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.
| Author | : Paul Orland |
| Publisher | : Manning Publications |
| Total Pages | : 686 |
| Release | : 2021-01-12 |
| Genre | : Computers |
| ISBN | : 1617295353 |
In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks
| Author | : Anthony Scopatz |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 567 |
| Release | : 2015-06-25 |
| Genre | : Science |
| ISBN | : 1491901586 |
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
