Using Jupyter Notebooks for Data Science Analysis in Python

Category: Tutorial


Posted on 2018-05-28, by voska89.

Description




Using Jupyter Notebooks for Data Science Analysis in Python
MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 2 Hours | 4.44 GB
Genre: eLearning | Language: English




Lesson 1: Project Jupyter and the Jupyter Ecosystem
Learning objectives
1.1 What are Project Jupyter and the Jupyter Notebook?
1.2 How Jupyter facilitates collaboration and sharing in data science
1.3 Differentiate between the Jupyter Notebook and other Jupyter projects
1.4 Find resources and connect with the Jupyter community through Jupyter.org
1.5 Learn through example using the Gallery of Interesting Jupyter Notebooks and GitHub
1.6 Contribute to the Jupyter ecosystem via GitHub
1.7 Participate in open source computing through NumFOCUS

Lesson 2: Creating Data Science Analyses in the Jupyter Notebook
Learning objectives
2.1 Determine which Python version to install
2.2 Install Jupyter using the Anaconda distribution of Python
2.3 Start your Jupyter Notebook using the command-line interface (CLI)
2.4 Start your Jupyter Notebook using the Anaconda Navigator
2.5 Run an ephemeral Interactive Jupyter Notebook on the web
2.6 Run Jupyter Notebooks in the cloud using Azure Notebooks
2.7 Run Jupyter Notebooks using Nteract
2.8 Navigate the Jupyter Notebook environment
2.9 Maintain good notebook hygiene
2.10 Perform quantitative exploratory data analysis (EDA) in your Jupyter Notebook using Python
2.11 Perform Visual Exploratory data analysis (EDA) in your Jupyter Notebook using Python
2.12 Create Jupyter Notebooks with different kernels (including R)
2.13 Install the R kernel

Lesson 3: Sharing Jupyter Notebooks
Learning objectives
3.1 Work with .ipynb files
3.2 Install nbconvert
3.3 Convert your Jupyter Notebook to different formats: HTML, PDF, and .py
3.4 Create dynamic presentation slides from your Jupyter Notebook using RISE
3.5 Share Jupyter Notebooks using GitHub and nbviewer
3.6 Access Jupyter Notebooks using Azure Notebooks
3.7 Compare and merge Jupyter Notebooks with nbdime

Lesson 4: Exploring New Jupyter Projects In-Depth
Learning objectives
4.1 Understand the basics of JupyterHub
4.2 Install and explore JupyterLab
4.3 Work with others using Real Time Collaboration
4.4 Enhance your analysis with interactive Jupyter Widgets
4.5 Share custom environments with Binder and BinderHub











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