Welcome to my personal GitHub repository showcasing the results of my hard work and dedication in the "Supervised Machine Learning: Regression and Classification" course offered by DeepLearning.AI and Stanford University. This repository serves as a testament to my journey through the world of machine learning, focusing on regression and classification tasks.
Within this repository, you will find a collection of the tasks and assignments I completed during the course, reflecting my progress and growth as a machine learning enthusiast. These tasks encompass a range of supervised machine learning challenges, including predictive modeling and binary classification.
- Task Implementations: Browse through the code and documentation that I've created to solve specific tasks and assignments from the course.
- Model Building: Gain insights into my approach to building machine learning models in Python, using libraries like NumPy and scikit-learn.
- Regression and Classification: Explore my work on linear regression, logistic regression, and other techniques taught in the course.
This repository is more than just code; it's a testament to my commitment to learning and applying machine learning in real-world scenarios. By sharing my work here, I hope to inspire others and demonstrate the skills I've acquired throughout the course.
I invite you to explore my repository, review my solutions, and provide feedback or suggestions. Feel free to engage with the code, ask questions, or share your own insights. Let's learn and grow together in the exciting field of machine learning!
Thank you for being a part of my journey, and I look forward to the collaborations and discussions that may arise from this shared learning experience.