🔟 Free useful resources to learn Machine Learning

👉 Google

https://developers.google.com/machine-learning/crash-course

👉 Leetcode

https://leetcode.com/explore/featured/card/machine-learning-101

👉 Hackerrank

https://www.hackerrank.com/domains/ai/machine-learning

👉 Hands-on Machine Learning

https://t.me/datasciencefun/424

👉 FreeCodeCamp

https://www.freecodecamp.org/learn/machine-learning-with-python/

👉 Machine learning projects

https://t.me/datasciencefun/392

👉 Kaggle

https://www.kaggle.com/learn/intro-to-machine-learning

https://www.kaggle.com/learn/intermediate-machine-learning

👉 Geeksforgeeks

https://www.geeksforgeeks.org/machine-learning/

👉 Create ML Models

https://docs.microsoft.com/en-us/learn/paths/create-machine-learn-models/

👉 Machine Learning Test Cheat Sheet

https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/

Join @free4unow_backup for more free resources

ENJOY LEARNING 👍👍

🤖 Artificial Intelligence Project Ideas ✅

🟢 Beginner Level
⦁ Spam Email Classifier (train on labeled emails with Naive Bayes—super practical for real apps!)
⦁ Handwritten Digit Recognition (MNIST) (classic CNN starter using TensorFlow)
⦁ Rock-Paper-Scissors AI Game (add random choices or simple ML to beat players)
⦁ Chatbot using Rule-Based Logic (pattern matching for basic Q&A)
⦁ AI Tic-Tac-Toe Game (minimax algorithm for unbeatable play)

🟡 Intermediate Level
⦁ Face Detection & Emotion Recognition (OpenCV + pre-trained models for facial analysis)
⦁ Voice Assistant with Speech Recognition (integrate SpeechRecognition lib for commands)
⦁ Language Translator (using NLP models) (Hugging Face transformers for quick translations)
⦁ AI-Powered Resume Screener (NLP to parse and score resumes)
⦁ Smart Virtual Keyboard (predictive typing) (build next-word prediction with basic RNNs)

🔴 Advanced Level
⦁ Self-Learning Game Agent (Reinforcement Learning) (Q-learning for games like CartPole)
⦁ AI Stock Trading Bot (time-series forecasting with LSTM)
⦁ Deepfake Video Generator (Ethical Use Only) (GANs like StyleGAN—handle responsibly)
⦁ Autonomous Car Simulation (OpenCV + RL) (pathfinding in virtual environments)
⦁ Medical Diagnosis using Deep Learning (X-ray/CT analysis) (CNNs on datasets like ChestX-ray)

💬 Double Tap ❤️ for more! 💡🧠

Free Resources to learn Python Programming
👇👇
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L

Being a Generalist Data Scientist won't get you hired.
Here is how you can specialize 👇

Companies have specific problems that require certain skills to solve. If you do not know which path you want to follow. Start broad first, explore your options, then specialize.

To discover what you enjoy the most, try answering different questions for each DS role:


- 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫
Qs:
“How should we monitor model performance in production?”

- 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 / 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭
Qs:
“How can we visualize customer segmentation to highlight key demographics?”

- 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭
Qs:
“How can we use clustering to identify new customer segments for targeted marketing?”

- 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐞𝐫
Qs:
“What novel architectures can we explore to improve model robustness?”

- 𝐌𝐋𝐎𝐩𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫
Qs:
“How can we automate the deployment of machine learning models to ensure continuous integration and delivery?”

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

ENJOY LEARNING 👍👍