DeepLearning and Deep-Learning-From-Scratch
These are **competitors** — both are educational repositories that teach deep learning fundamentals through implemented code examples from scratch, targeting the same audience of learners seeking to understand neural networks at a foundational level rather than using high-level frameworks.
About DeepLearning
DataForScience/DeepLearning
Deep Learning From Scratch
This project provides code and slides for an online webinar series on deep learning. It teaches the theoretical foundations and core ideas of deep learning in a hands-on way, using examples structured similarly to Keras. Aspiring data scientists, machine learning engineers, or researchers looking to understand and implement neural networks from the ground up would find this useful.
About Deep-Learning-From-Scratch
emilwallner/Deep-Learning-From-Scratch
Six snippets of code that made deep learning what it is today.
This resource provides foundational code examples to understand how deep learning algorithms work from the ground up. It takes mathematical concepts like cost functions and gradient descent, and translates them into simple, executable code snippets. This is ideal for students, educators, or researchers who want to grasp the core mechanics behind deep neural networks.
Scores updated daily from GitHub, PyPI, and npm data. How scores work