OpenTube

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

Infinite Codes

439,201 views

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

#########################################
I just started my own Patreon, in case you want to support!
Patreon Link: Patreon: InfiniteCodes
#########################################

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 Learn Machine Learning Like a GENIUS and N...
All Machine Learning Beginner Mistakes explained in 17 Min All Machine Learning Beginner Mistakes exp...
All Machine Learning Concepts Explained in 22 Minutes All Machine Learning Concepts Explained in...
All Machine Learning algorithms explained in 17 min All Machine Learning algorithms explained ...
The Math that make Machine Learning easy (and how you can learn it) How Math makes Machine Learning easy (and ...
15 Machine Learning Lessons I Wish I Knew Earlier 15 Machine Learning Lessons I Wish I Knew ...

Machine Learning Playlist: Machine Learning & Data Science

Machine Learning & AI in 100 seconds: Machine Learning & AI in 100 seconds

Git/Github Playlist:
Git / GitHub How To Videos

Python Tutorials for Beginner Data Scientists:Python Tutorials for Beginners

AWESOME github repos that help you get started:
https://github.com/data-flair/machine...
https://github.com/shsarv/Machine-Lea...
https://www.projectpro.io/article/mac...
https://github.com/ashishpatel26/500-...
https://github.com/gimseng/99-ML-Lear...
https://github.com/aswintechguy/Machi...
https://github.com/practical-tutorial...
https://github.com/NirantK/awesome-pr...
https://github.com/Nyandwi/machine_le...
https://github.com/recodehive/machine...
https://github.com/danistefanovic/bui...

================== 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)

20 Comments

@divyanshpandey8355 1 year ago

May your models never overfit: That's a real blessing right there folks

@docvm 1 year ago

1. EDA Portfolio
2. IRIS Dataset
3. Build your own Linear Regression
4. Titanic Survival Prediction
5. Housing Price Predictor
6. Image Classification System
7. Sentiment Analysis System
8. Customer Churn Predictor
9. Stock Price Predictor
10. Build your own Neural Network
11. Face Recognition System
12. Recommendation System
13. Automated ML Pipeline
14. Language Model from scratch
15. A/B Testing Framework
16. Image Generation System
17. Multi-language NLP Pipeline
18. Reinforcement Learning AI Game
19. Real Time Fraud Detection System
20. Build Your own AutoML
21. MLOps Pipeline
22. Distributed ML System

@madboymadstick4885 1 year ago

As someone trying to learn machine learning, this gives me somewhere to start and work towards. I am so glad this video got recommended to me. Thank you so much!

@monjishbhattacharyya3795 1 year ago

Fun fact about the linear regression project. Even without scikit, you don't need gradient descent. Look up pseudo-inverses and covariance matrices if you want to make accurate predictions without all the epochs (although it might take cubic time to run).

@yass-1323 1 year ago

"may your models never overfit" classic

@Noname-ok4tf 1 year ago

LOL we used the iris dataset in class. I thought it was about eyes.

@kinvert 1 year ago

Classifier predicting if your mom will like your project.

@ytann 1 year ago

See you next year with all 22. Thanks!

@nafizalmamun9855 1 year ago

"And you can show it to your mom".. Hell yeah!

@yass-1323 1 year ago

As someone starting from the statistical side of the realm of ML, this is quite inspiring

@adityapothulori4665 1 year ago

Gosh! All these projects seem to be A+ grade projects which definetly would give an edge to a portfolio. Thank you so much for this information.

@UniqueIndividual9000 1 year ago

Simple but useful information, even for someone at an intermediate level who needs to start building projects for their portfolio.

@justsurvivin8860 1 year ago

i love how my mom is very significant for all my ai projexts <3

@MrBodydriver 1 year ago

So I guess I jumped in the deep end by building my own Q-learning environment from scratch. No wonder it gave me so many headaches! Maybe I'll check out that Titanic project again...

@gabriella8623 1 year ago

Few years ago I trained a model based on detective stories. The result was very funny and I learned a lot about input data....

Prompt: Are you a killer?
Respond: That was necessarily!

@drsnehaljk 1 year ago

This is just awesome! as a self learner I do get concerned about knowledge gaps..this hands-on experience will help me. Thanks for showing a path. Waiting for next videos!

@study1134 3 months ago

awesome video, helped a lot!

@roeiohayon4501 1 year ago

Something really fun I worked on as personal project was image colorization, a great paper that I took inspiration from was Colorful Colorization by Richard Zhang.

@Vaishnav-n5z 1 year ago

Hey! I'm a 2nd year Computer Engineering student and already familiar with Docker, AWS, and Python. I was just starting to think about pivoting into MLOps, and your video gave me a great starting point. Really appreciate the beginner project suggestions — planning to start with EDA Portfolio and Iris Classification. Subscribed and looking forward to more!