Jupyter for Data Science [Video]

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MP4 | Video: h264, 1280x720 | Audio: AAC, 48kHz, 2 Ch | Duration: 3 Hours | 756 MB
Genre: eLearning | Language: English

Video Description
Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create documents that contain live code, equations, and visualizations.

This video course is a comprehensive guide to getting started with data science using the popular Jupyter Notebook. If you are familiar with Jupyter Notebook and want to learn how to use its capabilities to perform various data science tasks, this video course is for you! From data exploration to visualization, this course will take you every step of the way in implementing an effective data science pipeline using Jupyter. You will also see how you can utilize Jupyter's features to share your documents and codes with your colleagues. The course also explains how Python 3, R, and Julia can be integrated with Jupyter for various data science tasks.

By the end of this course, you will comfortably leverage the power of Jupyter to perform various tasks in data science successfully.

Style and Approach
This course is a perfect blend of concepts and practical examples and is very easy to understand and implement. It follows a logical flow where you will be able to build on your understanding of the different Jupyter features with every section.

Table of Contents
JUPYTER CONCEPTS
OPTIMIZING JUPYTER NOTEBOOKS
WORKING WITH ANALYTICAL DATA ON JUPYTER
DATA VISUALIZATION AND PREDICTION
DATA MINING AND SQL QUERIES
R WITH JUPYTER
DATA WRANGLING
JUPYTER DASHBOARDS
STATISTICAL MODELING
MACHINE LEARNING USING JUPYTER

What You Will Learn
Understand why Jupyter Notebooks are a perfect fit for your data science tasks
Perform scientific computing and data analysis tasks with Jupyter
Interpret and explore different kinds of data visually with charts, histograms, and more
Extend SQL's capabilities with Jupyter Notebooks
Combine the power of R and Python 3 with Jupyter to create dynamic notebooks
Create interactive dashboards and dynamic presentations
Master the best coding practices and deploy your Jupyter Notebooks efficiently

Authors
Dan Toomey
Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
Screenshots

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