Bøger af Matt Harrison

With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. Youll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics.This pocket reference includes sections that cover:Classification, using the Titanic datasetCleaning data and dealing with missing dataExploratory data analysisCommon preprocessing steps using sample dataSelecting features useful to the modelModel selectionMetrics and classification evaluationRegression examples using k-nearest neighbor, decision trees, boosting, and moreMetrics for regression evaluationClusteringDimensionality reductionScikit-learn pipelines

Introducing Your Guide to Learning PythonIllustrated Guide to Learning Python is designed to bring developers and others who are anxious to learn Python up to speed quickly. Not only does it teach the basics of syntax, but it condenses years of experience. You will learn warts, gotchas, best practices and hints that have been gleaned through the years in days. You will hit the ground running and running in the right way.Learn Python QuicklyPython is an incredible language. It is powerful and applicable in many areas. It is used for automation of simple or complex tasks, numerical processing, web development, interactive games and more. Whether you are a programmer coming to Python from another language, managing Python programmers or wanting to learn to program, it makes sense to cut to the chase and learn Python the right way. You could scour blogs, websites and much longer tomes if you have time. Treading on Python lets you learn the hints and tips to be Pythonic quickly.Packed with Useful Hints and TipsYou'll learn the best practices without wasting time searching or trying to force Python to be like other languages. I've collected all the gems I've gleaned over years of writing and teaching Python for you.A No Nonsense Guide to Mastering Basic PythonPython is a programming language that lets you work more quickly and integrate your systems more effectively. You can learn to use Python and see almost immediate gains in productivity and lower maintenance costs.What you will learn: Distilled best practices and tipsHow interpreted languages workUsing basic types such as Strings, Integers, and FloatsBest practices for using the interpreter during developmentThe difference between mutable and immutable dataSets, Lists, and Dictionaries, and when to use eachGathering keyboard inputHow to define a classLooping constructsHandling Exceptions in codeSlicing sequencesCreating modular codeUsing librariesLaying out codeCommunity prescribed conventions

Python is easy to learn. You can learn the basics in a day and be productive with it. But there are more advanced constructs that you will eventually run across if you spend enough time with it. These constructs, while not necessary per se, allow you to be more succinct, re-use code, and think about code in a different way. This book covers many of these intermediate constructs: * Functional programming * List comprehensions * Generator expressions * Set & dict comprehensions * Iteration * Generators * Closures * Decorators I have taught these constructs at popular tutorials at PyCon and other conferences. This book is based on my experience teaching and using Python for many years. I hope you learn something while in the course of your reading. Maybe it will help you in your next task, code review, or job interview.

A new edition of the bestselling Pandas cookbook updated to pandas 1.x with new chapters on creating and testing, and exploratory data analysis. Recipes are written with modern pandas constructs. This book also covers EDA, tidying data, pivoting data, time-series calculations, visualizations, and more.