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Author:   Philipp Kats ,  David Katz
Publisher:   Packt Publishing Limited
Imprint:   Packt Publishing Limited
ISBN:  

9781789535365

ISBN 10:   1789535360
Pages:   482
Publication Date:   30 August 2019
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In stock  
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Table of Contents

Table of Contents Preparing the workspace First Steps in coding variables and data types Functions Data Structures Loops and other compound statements First script: Geocoding with Web APIs Scraping Data from the Web with Beautiful Soup 4 Simulation with Classes and inheritance Shell, Git, Conda, and More at Your Command Python for Data Applications Data cleaning and manipulation Data Exploration and Visualization Training a Machine Learning model Improving your Models Metrics pipelines and experiments Packaging and testing with poetry and pytest Data Pipelines with Luigi Lets build a dashboard Serving models with Rest API Serverless API using Chalice Best practices and Python performance

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Author Information

Philipp Kats is a researcher at the Urban Complexity Lab, NYU CUSP, a research fellow at Kazan Federal University, and a data scientist at StreetEasy, with many years of experience in software development. His interests include data analysis, urban studies, data journalism, and visualization. Having a bachelor's degree in architectural design and a having followed the rocky path (at first) of being a self-taught developer, Philipp knows the pain points of learning programming and is eager to share his experience. David Katz is a researcher and holds a Ph.D. in mathematics. As a mathematician at heart, he sees code as a tool to express his questions. David believes that code literacy is essential as it applies to most disciplines and professions. David is passionate about sharing his knowledge and has 6 years of experience teaching college and high school students.

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