Thread by @TheOyinbooke

MODULE 2: How to BUILD a robust Machine Learning Portfolio for a Beginner 🧵

1. Where Do I find datasets for personal projects?
2. How to Identify What Use Case fits a Sample Data
3. Creating A Fictitious Business Use Case

40 Sample Datasets
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Before we continue, make sure you check out Module 1 THREAD with the Link below:

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https://twitter.com/TheOyinbooke/status/1495419412920389643?s=20&t=DSGuKzbjZDWOSVM39hSLew

Where to get Datasets for your sample projects
No 1: Kaggle

In this video, I did a walkthrough on how to get sample projects from Kaggle Datasets.

Don't forget to do the assignment at the end of the video
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This is the link to the Kaggle datasets page
kaggle.com/datasets

Check the video above for the walkthrough and the take-home assignment.

#MLPortfolioOnBirdApp

Where to get Datasets for your sample projects
No 2: UCI Machine Learning Repository

Check out this video to see samples of project data from the UCI Machine Learning Repository

Make sure you do your assignment
#MLPortfolioOnBirdApp

This is the link to the UCI Machine Learning Repository

Check the video above for the walkthrough and the take-home assignment.

archive.ics.uci.edu/ml/index.php

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Where to get Datasets for your sample projects
No 3: OPEN ML Datasets

Check out this video to see samples of project data from the OPEN ML Dataset

Make sure you do your assignment
#MLPortfolioOnBirdApp

This is the link to the OPEN ML Dataset repository
openml.org/home
Check the video above for the walkthrough and the take-home assignment.

#MLPortfolioOnBirdApp

Where to get Datasets for your sample projects
No 4: DATA Flair Training Blog

Check out this video to see samples of project data from the Data Flair Training Blog Post

Make sure you do your assignment
#MLPortfolioOnBirdApp

This is the link to the Data Flair Training Blog Post
data-flair.training/blogs/machine-…

Check the video above for the walkthrough and the take-home assignment.

#MLPortfolioOnBirdApp

Module 2 is in three (3) Parts.
The next content will be on "How to identify ML use case that is the best fit for a given dataset"

Do Like, Retweet, and Share Main THREAD🧵 with others.
I am counting on YOU

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