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Beginning Data Science with Python and Jupyter

Beginning Data Science with Python and Jupyter
.MP4, AVC, 400 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 2h 49m | 723 MB
Instruct: Chris Dalla Villa

Perfm reproducible data analyses with these data explation tools

Getting started with data science doesn't have to be an uphill battle. This step-by-step video course is ideal f beginners who know a little Python and are looking f a quick, fast-paced introduction. Get to grips with the skills you need f 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 exple machine learning models with real datasets to give you the skills and exposure you need f the real wld.We'll start with understanding the basics of Jupyter and its standard features. You'll be analyzing an example of a data analytics rept. After analyzing a data analytics rept, next step is to implement multiple classification algithms. 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.

What You Will Learn

Identify potential areas of investigation and perfm explaty 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 transfm it into Pandas DataFrames
Create interactive, web-friendly visualizations to clearly communicate your findings

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Beginning Data Science with Python and Jupyter

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Tags: Beginning, Science, Python, Jupyter

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