Data Science your first day
1800:00 Intro
02:02 Data Science Project Structure Overview
05:15 Create Github Repo
07:28 Launch Github Codespaces
11:34 Using Colab Notebook
12:47 Using TOC in Colab Notebook
14:43 Saving notebook to Colab to Github
19:52 Ingesting CSV files into Colab
22:31 Describing Data using df.describe()
24:30 Plotting data with seaborn
28:30 lmplot
29:30 Comparing cumulative deaths in Covid19 plot by state
32:40 Merging Pandas Dataframe with election and Sugar Consumption
37:38 Exporting CSV file and uploading to Github from Colab result
39:27 Continuous Integration of Jupyter Notebook with Github Actions
40:44 Create Makefile
44:32 Using Github Actions to test Jupyter via nbval plugin
45:43 Using Github Status Badge for Jupyter Notebook test run pass
If you enjoyed this video, here are additional resources to look at:
Coursera + Duke Specialization: Building Cloud Computing Solutions at Scale Specialization: https://www.coursera.org/specializations/building-cloud-computing-solutions-at-scale
O'Reilly Book: Practical MLOps: https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017
O'Reilly Book: Python for DevOps: https://www.amazon.com/gp/product/B082P97LDW/
Pragmatic AI: An Introduction to Cloud-based Machine Learning: https://www.amazon.com/gp/product/B07FB8F8QP/
Pragmatic AI Labs Book: Python Command-Line Tools: https://www.amazon.com/gp/product/B0855FSFYZ
Pragmatic AI Labs Book: Cloud Computing for Data Analysis: https://www.amazon.com/gp/product/B0992BN7W8
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Pragmatic AI Book: Minimal Python: https://www.amazon.com/gp/product/B0855NSRR7
Pragmatic AI Book: Testing in Python: https://www.amazon.com/gp/product/B0855NSRR7
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