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lgli/Fabrizio Romano & Benjamin Baka & Dusty Phillips - Getting Started With Python: Understand Key Data Structures and Use Python in Object-Oriented Programming (2019, Packt Publishing).mobi
Getting Started with Python : Understand Key Data Structures and Use Python in Object-oriented Programming 🔍
Fabrizio Romano & Benjamin Baka & Dusty Phillips Packt Publishing, Limited, Packt Publishing, Birmingham, UK, 2019
英语 [en] · MOBI · 7.5MB · 2019 · 📘 非小说类图书 · 🚀/lgli/zlib · Save
描述
Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting information Key Features Turn your designs into working software by learning the Python syntax Write robust code with a solid understanding of Python data structures Understand when to use the functional or the OOP approach Book Description This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You'll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you've covered core topics, you'll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: Learn Python Programming - Second Edition by Fabrizio Romano Python Data Structures and Algorithms by Benjamin Baka Python 3 Object-Oriented Programming by Dusty Phillips What you will learn Use data structures and control flow to write code Use functions to bundle together a sequence of instructions Implement objects in Python by creating classes and defining methods Design public interfaces using abstraction, encapsulation and information hiding Raise, define, and manipulate exceptions using special error objects Create bulletproof and reliable software by writing unit tests Learn the common programming patterns and algorithms used in Python Who this book is for If you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP. Downloading the example code for this book You can download th ..
备用文件名
zlib/Computers/Programming/Fabrizio Romano & Benjamin Baka & Dusty Phillips/Getting Started With Python: Understand Key Data Structures and Use Python in Object-Oriented Programming_19084513.mobi
备选标题
Python Data Science Essentials : A Practitioner’s Guide Covering Essential Data Science Principles, Tools, and Techniques, 3rd Edition
备选标题
Applied Data Science with Python and Jupyter : Use Powerful Industry-standard Tools to Unlock New, Actionable Insights From Your Data
备选作者
Romano, Fabrizio, Baka, Benjamin, Phillips, Dusty
备选作者
Boschetti, Alberto, Massaron, Luca
备选作者
Alberto Boschetti; Luca Massaron
备选作者
Galea, Alex
备选作者
Alex Galea
备用版本
United Kingdom and Ireland, United Kingdom
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Place of publication not identified, 2018
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Place of publication not identified, 2019
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Packt Publishing, Birmingham, UK, 2018
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Third edition, Birmingham, UK, 2018
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Learning path, Birmingham, 2019
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Packt Publishing, [N.p.], 2018
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Birmingham, England, 2018
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Birmingham, England, 2019
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1st edition, 2018
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Oct 31, 2018
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Sep 28, 2018
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2018-10-31
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2018-09-28
元数据中的注释
lg2865371
备用描述
Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications. Key Features Get up and running with the Jupyter ecosystem and some example datasets Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests Discover how you can use web scraping to gather and parse your own bespoke datasets Book Description Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations. What you will learn Get up and running with the Jupyter ecosystem Identify potential areas of investigation and perform exploratory data analysis Plan a machine learning classification strategy and train classification models Use validation curves and dimensionality reduction to tune and enhance your models Scrape tabular data from web pages and transform it into Pandas DataFrames Create interactive, web-friendly visualizations to clearly communicate your findings Who this book is for Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries such as Pandas, Matplotlib, and Pandas providing you a useful head start. 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 thisbook elsewhere, you can visit http://www.PacktPub.com/support and regi ..
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Gain useful insights from your data using popular data science toolsKey FeaturesA one-stop guide to Python libraries such as pandas and NumPyComprehensive coverage of data science operations such as data cleaning and data manipulationChoose scalable learning algorithms for your data science tasksBook DescriptionFully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn.The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You'll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost.By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business usersWhat you will learnSet up your data science toolbox on Windows, Mac, and LinuxUse the core machine learning methods offered by the scikit-learn libraryManipulate, fix, and explore data to solve data science problemsLearn advanced explorative and manipulative techniques to solve data operationsOptimize your machine learning models for optimized performanceExplore and cluster graphs, taking advantage of interconnections and links in your dataWho this book is forIf you're a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle real-world data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts covered in this book.
备用描述
Applied Data Science with Python and Jupyter teaches you the skills you need for entry-level data science. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. You'll ...
备用描述
Python Data Science Essentials, Third Edition provides modern insight in setting up and performing data science operations effectively using the latest python tools and libraries. It builds faster governance on the most essential tasks such as data munging and pre-processing, along with all the techniques you require.
备用描述
This Learning Path is a thorough and practical introduction to Python. You will learn all about Python data structures, its most common algorithms, and its objects, and use all these to create clever applications that will transform your business.
开源日期
2022-01-29
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