Table of Contents:
- 1. Introduction
- 2. Resources
- 3. Advice
- 4. Ending Note
Hey y'all! I'm Vincent a 2nd year at 6th college studying Computer Science with a heavy interest in AI. Below I've provided some resources and advice. These lists are non-comprehensive. But for now, they are great starting points if you want to learn more on your own or for your project!
📌 Note: The following list is not comprehensive and are only suited for deep learning.
Deep Learning:
- Deep Learning Crash Course for Beginners by freeCodeCamp covers just the conceptual basics of deep neural networks.
- Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial by deeplizard provided by freeCodeCamp covers deep learning with a concentration on computer vision models. It focuses on practical implementation (with TensorFlow and Keras) rather than math.
- Introduction | Deep Learning Tutorial 1 (Tensorflow Tutorial, Keras & Python) by codebasics covers a myriad of topics, covering concepts and their implementations in TensorFlow and Keras.
- TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial by TechWithTim provided by freeCodeCamp briefly covers concepts while focusing mainly on the code implementation in TensorFlow and Keras.
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron is a comprehensive book for breaking into machine learning and deep learning. Part II of the book covers deep learning with TensorFlow and Keras.
- PyTorch Tutorials by Aladdin Persson offers a code-centric guide to learning deep learning with the PyTorch framework.
- Toy with the code. Experiment with it and see how it works.
- If you read Aurélien Géron's book, I advise you to do the exercises and organize your code in this repo!
- Tutorial hell is a commonly thrown around phrase describing the difficulties of the wealth of tutorials available to you. Some are confusing. Sometimes there are too many. Some are not comprehensive. Some don't include the information you want. Sometimes there are too many tutorials and it seems as if your progression has been halted. My advice is simply to pick a reliable source. Stick with it. Navigate through other tutorials if needed, but look elsewhere to learn more once you have mastered your fundamentals.
- Start small and work your way up. Start by learning the basics, implementing basic projects. Then, once you've grown comfortable with this cycle, upgrade to more advanced knowledge until you are ready to tackle your project.
Making a great project is cool. Making new friends, learning new things, and leaving with curiosity is better. Have fun with the project. Collaborate and meet up. Struggle and learn together.