"Completing this course has been an incredible learning experience, covering everything from supervised and unsupervised learning to reinforcement learning and advanced algorithms like decision trees and tree ensembles. The highlight for me was understanding how to tackle overfitting and underfitting, and knowing exactly what to do (and not do) when my models face high bias or high variance. It's a little disappointing about the Coursera policy change and not getting the certificate, but the wealth of knowledge gained far outweighs that. A big thank you to Coursera, Andrew Ng, and Stanford Online for this fantastic course!"
- 🧠 Supervised Learning: Mastered linear and logistic regression, building predictive models for various tasks.
- 🤖 Neural Networks: Built and trained neural networks with TensorFlow for multi-class classification.
- 🌳 Decision Trees & Ensembles: Explored decision trees, random forests, and boosting techniques for robust models
- 🕵️♀️ Unsupervised Learning: Applied clustering and anomaly detection to uncover hidden patterns in data
- 🛍️ Recommender Systems: Built recommender systems using collaborative filtering and content-based approaches.
- 🤖 Deep Reinforcement Learning: Delved into the world of deep reinforcement learning, training agents to make optimal decisions.
