Building a Neural Network Framework from Scratch in C++ | Full Demo + Code Walkthrough

In this video, I showcase my custom neural network framework built entirely in C++. I walk through everything from setup to implementation, including: Live demos: - A CNN running on MNIST for handwritten digit recognition - A regression example showing off flexibility Full framework overview: -How to build models with the framework -Code architecture breakdown -Layer creation, forward/backward propagation, optimizers -How training works under the hood (no frameworks—just C++) This project was built to learn the nuts and bolts of deep learning—no shortcuts, full control, high performance. GitHub: https://github.com/jalenfran/JNet Website: https://www.jalencode.com/ LinkedIn: https://www.linkedin.com/in/jalen-francis/ #Cplusplus #NeuralNetwork #MachineLearning #DeepLearning #FromScratch #Coding #ai Chapters: 0:00 Intro 0:23 Network Class 2:07 Tensor Class 3:02 Layer Classes 4:48 Optimizers 5:26 Code Optimizations 6:22 Network Examples 9:08 MNIST Recognition Model 12:12 In-depth Code Overview 12:28 Activation 13:27 Convolutional Layer 14:25 Flattening Layer 14:53 Pooling Layer 15:49 Wrap up and conclusions