Welcome to my repository for solutions to the lab exercises from the MIT 6.S191 course: Introduction to Deep Learning. Here, I will be sharing my personal solutions, additional comments, and modifications to the lab assignments provided by the course.
This repository serves as a space for me to work through the MIT 6.S191 lab exercises. Each lab includes various coding exercises, which are designed to build foundational skills in deep learning. You’ll find my step-by-step solutions, insights, and additional comments that I have added to the original code, as well as any modifications necessary for my understanding and exploration.
The course materials I’m working with, including lab exercises, were created by MIT 6.S191 and are licensed under the MIT License. I have adapted them here strictly for educational and personal learning purposes, with the necessary attributions provided in each notebook.
My main goal is to use this repository as a learning tool to develop new competencies in artificial intelligence and deep learning. Working through these exercises will help me deepen my understanding of neural networks, optimization techniques, data handling, and model evaluation, as well as hands-on implementation skills in Python and popular deep learning frameworks.
This process will be invaluable as I build the technical foundation and problem-solving skills essential for more advanced work in AI. By carefully documenting my solutions and thoughts, I aim to create a useful reference that I can revisit and expand upon as I continue to grow in this field.
I would like to thank the MIT 6.S191 team for creating and sharing such valuable resources for learning deep learning. You can find more about the course here.
I’m excited to continue working through these labs and to see how much I can learn and improve throughout this journey!