Devlog #004

Hey everyone!

Today I made a major upgrade to the neural network. The biggest additions were Dropout and Batch Normalization, which help the model generalize better and make training more stable. I also redesigned the architecture, making it much deeper and larger than before.

Implementing these features wasn’t easy, it took a lot of debugging and experimentation, but the results were definitely worth the effort.

Results

Accuracy: 98.26%

Training is now noticeably slower due to the increased complexity of the network, but I’m very happy with the improvement in performance.

The next step is to build a clean and interactive UI so that anyone can better understand how a neural network learns and makes predictions in real time.

Thanks for reading, and see you in the next devlog!