Jupyter Notebook for Data Science Teams

Jupyter Notebook for Data Science Teams
Jupyter Notebook for Data Science Teams
English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 3 Hours | 758 MB

In this Jupyter Notebook for Data Science Teams training course, expert author Jonathan Whitmore will teach you about Jupyter Notebook extensions, widgets, and team sharing. This course is designed for data scientists who need to collaborate on projects.

You will start by learning how to install and set up the Jupyter Notebook, as well as how to set up Git and GitHub accounts. From there, Jonathan will teach you about Jupyter Notebook features, including extensions, SQL Magic and Pandas, and interactive widgets. This video tutorial also covers how to share notebooks with a team. Finally, you will run through an example of using a single Git repository for a team data science project from start to finish.

Once you have completed this computer based training course, you will have learned how to use Jupyter Notebook for data science teams.

Table of Contents

1. Introduction
Introduction And Course Overview
About The Author
How To Access Your Working Files

2. Setting Up Environment
Installing The Jupyter Notebook And Setup
Setting Up Git And GitHub Account

3. Jupyter Notebook Features
Standard Browser Use
Installing Notebook Extensions
More On Notebook Extensions
SQL Magic And Pandas
R In Jupyter Notebook
Autocreate Documents In HTML Or PDF
Interactive Widgets
Bleeding Edge JupyterHub

4. Sharing Notebooks With A Team
Organizing A Workflow
Lab Vs. Deliverable Notebook
Directory Structure And Naming Conventions
Version Control

5. Project Data Science With The Notebook EndToEnd Example
Get Data
Load The Data
Initial Data Cleaning
Creating A New Github Repository
Version Control
Exploratory Data Analysis Regression Plotting
Exploratory Data Analysis Variable Transformations
Git Branch Store Data Cleaned Pipeline
Feature Engineering
Random Forest Prediction And Evaluation
Final Analysis Cleanup
Pull Request, Peer Review, And Merge With Master

6. Project Data Science Statistics And Data Visualizations
Initial Data Visualization
Advanced Pandas Plotting
Advanced Seaborn Plotting
Statsmodels Analysis Part 1
Statsmodels Analysis Part 2

7. Conclusion
Resources And Where To Go From Here