by Chris Dalla Villa, Alex Galea | Released September 2018 | ISBN: 9781789532449

Perform reproducible data analyses with these data exploration toolsAbout This VideoGet up and running with the Jupyter ecosystem and some example datasetsLearn about key machine learning concepts like SVM, KNN classifiers and Random ForestsDiscover how you can use web scraping to gather and parse your own bespoke datasetsIn DetailGetting started with data science doesn't have to be an uphill battle. This step-by-step video course is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. 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.We'll start with understanding the basics of Jupyter and its standard features. You'll be analyzing an example of a data analytics report. After analyzing a data analytics report, next step is to implement multiple classification algorithms. We'll then show you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Finish up by learning to visualize these data interactively Show and hide more

1. Chapter 1 :
   • Title Overview 00:07:37
   • Lesson Overview 00:03:36
   • Basic Functionality 00:30:01
   • Useful Features of Jupyter 00:13:11
   • Python Libraries 00:06:07
   • Our First Analysis - The Boston Housing Dataset 00:13:31
   • Introduction to Predictive Analytics 00:13:34
   • Lesson Summary 00:00:52
2. Chapter 2 : Lesson 2: Data Cleaning and Advanced Machine Learning
   • Lesson Overview 00:03:09
   • Preparing to Train a Predictive Model 00:11:16
   • Preparing to Train a Predictive Model 00:13:05
   • Training Classification Models 00:09:34
   • K-Fold Cross-Validation 00:12:37
   • Lesson Summary 00:00:26
3. Chapter 3 : Lesson 3: Web Scraping and Interactive Visualizations
   • Lesson Overview 00:04:01
   • Scraping Web Page Data 00:16:48
   • Interactive Visualizations 00:07:52
   • Lesson Summary 00:01:44
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