Introduction to Neural Networks — Machine Learning Roadmap
A bridge into deep learning: enough to know when it's the right tool
Steps in Introduction to Neural Networks
- Perceptrons & the Building Blocks of Neural Networks — advanced · The simplest possible neural unit and how it makes a decision
- Feedforward Neural Networks Basics — advanced · Stacking layers of neurons to model more complex, non-linear relationships
- Activation Functions — advanced · ReLU, sigmoid and tanh, and why non-linearity matters
- Backpropagation Intuition — advanced · How a neural network's weights are updated based on its errors
- When to Use Classical ML vs Neural Networks — advanced · Matching model complexity to data size, structure and the problem itself
Part of
- Machine Learning roadmap — the full learning path