22 Boost Your Data Science Skills with 22 Must-Try Machine Learning Projects 🚀

22 Machine Learning Projects That Will Make You A GOD At Data Science

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I wish I knew about these 22 machine learning projects when I started! Moving beyond basic Titanic datasets, I'll show you how to build everything from beginner-friendly Iris classifiers to advanced distributed ML systems. Each project is rated for difficulty, resume value, learning potential, and real-world impact - everything you need to build an impressive ML portfolio. Keywords: machine learning projects, portfolio projects, data science, ML engineering, AutoML, computer vision, NLP, MLOps.

Also Watch:
Learn Machine Learning Like a GENIUS and Not Waste Time https://youtu.be/qNxrPri1V0I
All Machine Learning Beginner Mistakes explained in 17 Min https://youtu.be/oMc9StPVzOU
All Machine Learning Concepts Explained in 22 Minutes https://youtu.be/Fa_V9fP2tpU
All Machine Learning algorithms explained in 17 min https://youtu.be/E0Hmnixke2g
The Math that make Machine Learning easy (and how you can learn it) https://youtu.be/wOTFGRSUQ6Q
15 Machine Learning Lessons I Wish I Knew Earlier https://youtu.be/espQDESe07w

Machine Learning Playlist: https://www.youtube.com/playlist?list=PLbdTl8vSSyUDAvDPc1r3j9itciu_kb5vG

Machine Learning & AI in 100 seconds: https://www.youtube.com/playlist?list=PLbdTl8vSSyUDWtx6ZRnfzU3jo0Kpd9CxX

Git/Github Playlist:
https://www.youtube.com/playlist?list=PLbdTl8vSSyUBJg6PI9AqfJBw8U0y9J3kY

Python Tutorials for Beginner Data Scientists:https://www.youtube.com/playlist?list=PLbdTl8vSSyUAJid3yaBjqcMrvLwhcM6vf

AWESOME github repos that help you get started:
https://github.com/data-flair/machine-learning-projects
https://github.com/shsarv/Machine-Learning-Projects
https://www.projectpro.io/article/machine-learning-projects-on-github/465
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
https://github.com/gimseng/99-ML-Learning-Projects
https://github.com/aswintechguy/Machine-Learning-Projects
https://github.com/practical-tutorials/project-based-learning
https://github.com/NirantK/awesome-project-ideas
https://github.com/Nyandwi/machine_learning_complete
https://github.com/recodehive/machine-learning-repos
https://github.com/danistefanovic/build-your-own-x

================== Timestamps ================
00:00 - Intro
00:54 - Exploratory Data Analysis (EDA) Portfolio (Beginner)
01:40 - Iris Flower Classification (Beginner)
02:49 - Build Your Own Linear Regression (Intermediate)
03:26 - Titanic Survival Prediction (Beginner)
04:07 - Housing Price Predictor (Beginner)
04:47 - Image Classification System (Intermediate)
05:29 - Sentiment Analysis System (Intermediate)
06:07 - Customer Churn Predictor (Beginner)
06:43 - Stock Price Predictor (Intermediate)
07:14 - Build Your Own Neural Network (Advanced)
07:49 - Real-time Face Recognition System (Advanced)
08:29 - Recommendation System (Intermediate)
08:54 - Automated ML Pipeline (Advanced)
09:21 - Language Model From Scratch (Advanced)
09:50 - A/B Testing Framework (Advanced)
10:21 - Image Generation System (Advanced)
10:49 - Multi-language NLP Pipeline (Advanced)
11:14 - Reinforcement Learning Game AI (Advanced)
11:38 - Real-time Fraud Detection System (Advanced)
12:10 - Build Your Own AutoML (Advanced)
12:38 - MLOps Pipeline (Advanced)
13:06 - Distributed ML System (Advanced)