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Learn Python by Building Data Science Applications
Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications: A fun, project-based guide to learning Python 3 while building real-world apps

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Learn Python by Building Data Science Applications

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Key benefits

  • Learn the basics of developing applications with Python and deploy your first data application
  • Take your first steps in Python programming by understanding and using data structures, variables, and loops
  • Delve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in Python

Description

Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.

Who is this book for?

If you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.

What you will learn

  • Code in Python using Jupyter and VS Code
  • Explore the basics of coding – loops, variables, functions, and classes
  • Deploy continuous integration with Git, Bash, and DVC
  • Get to grips with Pandas, NumPy, and scikit-learn
  • Perform data visualization with Matplotlib, Altair, and Datashader
  • Create a package out of your code using poetry and test it with PyTest
  • Make your machine learning model accessible to anyone with the web API

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 30, 2019
Length: 482 pages
Edition : 1st
Language : English
ISBN-13 : 9781789533064
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What do you get with eBook?

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Product Details

Publication date : Aug 30, 2019
Length: 482 pages
Edition : 1st
Language : English
ISBN-13 : 9781789533064
Category :
Languages :
Tools :

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Table of Contents

25 Chapters
Section 1: Getting Started with Python Chevron down icon Chevron up icon
Preparing the Workspace Chevron down icon Chevron up icon
First Steps in Coding - Variables and Data Types Chevron down icon Chevron up icon
Functions Chevron down icon Chevron up icon
Data Structures Chevron down icon Chevron up icon
Loops and Other Compound Statements Chevron down icon Chevron up icon
First Script – Geocoding with Web APIs Chevron down icon Chevron up icon
Scraping Data from the Web with Beautiful Soup 4 Chevron down icon Chevron up icon
Simulation with Classes and Inheritance Chevron down icon Chevron up icon
Shell, Git, Conda, and More – at Your Command Chevron down icon Chevron up icon
Section 2: Hands-On with Data Chevron down icon Chevron up icon
Python for Data Applications Chevron down icon Chevron up icon
Data Cleaning and Manipulation Chevron down icon Chevron up icon
Data Exploration and Visualization Chevron down icon Chevron up icon
Training a Machine Learning Model Chevron down icon Chevron up icon
Improving Your Model – Pipelines and Experiments Chevron down icon Chevron up icon
Section 3: Moving to Production Chevron down icon Chevron up icon
Packaging and Testing with Poetry and PyTest Chevron down icon Chevron up icon
Data Pipelines with Luigi Chevron down icon Chevron up icon
Let's Build a Dashboard Chevron down icon Chevron up icon
Serving Models with a RESTful API Chevron down icon Chevron up icon
Serverless API Using Chalice Chevron down icon Chevron up icon
Best Practices and Python Performance Chevron down icon Chevron up icon
Assessments Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.8
(4 Ratings)
5 star 25%
4 star 0%
3 star 0%
2 star 75%
1 star 0%
Hoi Nguyen Aug 17, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book with smart coding included!
Amazon Verified review Amazon
George Paquin Jun 14, 2024
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
So far, I've not been able to get Anaconda to install on linux mint. So my experience is. "What a pain". Might be a decent product, but so far it's disappointing. I think I'm going to have to set up a new system just to run it. Or find a linux mentor.
Feefo Verified review Feefo
Tony Apr 25, 2022
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
I am three quarters finished woth the book and there are many hurdles for a beginner of python. Number one the book uses an extremely complicated database about world war 2 battles. The database should have been less complicated since the book is supposedly meant for beginners of python. This complicated database is used again and again throughout the book for various tasks which impedes the learning process. Why couldn't the author have chosen a simpler database? The book starts out showing elements of the python language. At times the lessons are not bad. But then the author goes into this confusing complicated datascraping example which he uses for the next half of the book thereby confusing the reader. Why wasn't the datascraping explained to a beginner audience?? The section on data cleaning is super complicated using regex and was not explained well at all. I have about one quarter of the book left and I will update my review if i notice any improvement. The bottom line is that the author does not explain concepts to a beginner python audience like the book claims. He throws around terms like the reader is familiar with them like " pipes" without adequately explaining them. I am familiar with C and Java and I was still confused with the author's explanations. The bottom line: This is just NOT a book for python beginners and the explanations of real complicated concepts are lacking at best and down right confusing at worst.UPDATE: I continued to read the book and I just about gave up. From chapter 13 to the end gets progessively complicated and so disappointing, I had high hopes for this book to teach me python and data science at the same time, while it barely teaches either one. The problem here is that the author just does NOT explain every line of code. ANd the lines of code which he bothers to explain are not explained adequately. He just throws SUPER complicated code at you and expects you to understand it. On page 5 he states: " The book is designed for complete beginners..." Really?? If you are a beginner wouldn't you want every line of code explained? Or would you like the author to throw code at you and ASSUME you understand it? I wish this book would have been like the book: Artificial Intelligence and Deep Learning with Python: Every Line of Code Explained For Readers New to AI and New to Python. In that book each and every line of python code IS explained , profusely. I am extremely dissapointed.
Amazon Verified review Amazon
Ricardo Cavallí Feb 11, 2020
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
Quite a bit of the code does not work and the author doesn't respond to social media for help...I would return it if it wasn't digital.
Amazon Verified review Amazon
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