Learn How Neural Networks Work From Scratch
A blog illustrating how neural networks work, with example code in C++- Why Machine Learning And Neural Networks Matter
- What is a Neural Network?
- An Intro To Linear Regression Using One Neuron
- Linear Regression Using A Single Neuron Continued, The Learning Process
- Writing The Code For Linear Regression With A Single Neuron
- Combining Individual Neurons into a Feedforward Neural Network
- Writing The Code For A Feedforward Neural Network
- Designing a Modular Neural Network Library
- Tensors, The Building Block For Deep Learning
- Classifying Handwriting Digits With A Feed Forward Neural Network
- Optimizing Our Neural Network With Blas And Openmp
- Evaluation Pt 1: Evaluating MNIST Accuracy On The Test Set
- Improving Our Neural Network Outputs With Softmax Classification
- Using Mini Batches During Training
- Evaluation Pt 2: Precision And Recall Curves
- Other Activation Functions
- Saving And Loading Models
- Natural Language Processing With Neural Networks
- Word Embeddings
- Recurrent Neural Networks
- Text Classification
- Sentiment Analysis
- Named Entity Recognition
- Image Processing With Neural Networks
- Convolutional Neural Networks
- CIFAR-10 image classification
- Image Segmentation
- Combining NLP and Image Processing to Describe Images in Natural Language
- Generative Neural Networks
- GANS