Learning Rate Machine Learning #machinelearning #learningrate #datascience

Build a Supervised Learning Model from Scratch | Polynomial Regression with Gradient Descent in Python

In this video, we bring machine learning to life—from first principles to prediction—by building a supervised learning model from scratch using Python and a Jupyter Notebook.

You'll learn how to:

✅ Understand polynomial regression intuitively
✅ Implement gradient descent step by step
✅ Visualize predictions using Plotly
✅ Track model loss and improvement over time
✅ Make predictions on unseen data

No scikit-learn. No shortcuts. Just hands-on learning to help you master the core ideas!
📚 Related Videos:
🔍 What is Machine Learning?: https://youtu.be/w-ZzzWOFp-M
🤖 AI vs. ML vs. DL | Supervised, Unsupervised & Reinforcement Learning and Their Use Cases: https://youtu.be/UtHYovSv41U

🛠 Tools Used:
Python
NumPy
Plotly
Jupyter Notebook inside a Dev Container (VS Code)

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💬 Drop a comment if you have questions or want more content like this.

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