A dedicated space to share my journey of learning, documenting courses, and taking notes :)

Current Course: Machine Learning Specialization

Course Details

• Taught by: Instructor Andrew Ng
• Platform: Go To Course

What I’m Learning:

1. Foundations of Machine Learning
2. Supervised Learning (Regression, Classification)
3. Unsupervised Learning (Clustering, Dimensionality Reduction)
4. Neural Networks and Deep Learning
5. Practical skills for real-world AI applications.

My Notes

Course 1: Supervised Machine Learning: Regression and Classification

• Key Concepts:
  • Supervised vs. Unsupervised Learning
  • Applications of Machine Learning
  • Importance of Data Quality
• Notes: coming soon

Course 2: Advanced Learning Algorithms

• Key Concepts:
  • Hypothesis Function: ( h_\theta(x) = \theta_0 + \theta_1x )
  • Cost Function: Mean Squared Error (MSE)
  • Gradient Descent Algorithm
• Notes: WIP

Course 2: Advanced Learning Algorithms

• Key Concepts: WIP
• Notes: WIP

Course 3: Unsupervised Learning, Recommenders, Reinforcement Learning

• Key Concepts: WIP
• Notes: WIP

“AI is the new electricity.” – Andrew Ng

Stay tuned for more updates as I progress through the specialization! 🚀