Machine Learning Roadmap

1. What Machine Learning Actually Is
   Linear Algebra for ML (recommended)Calculus for ML (recommended)Probability for ML (recommended)Unsupervised & Reinforcement Learning (alternative option)ML Frameworks (PyTorch, TensorFlow) (recommended)
2. Ensemble Methods (recommended)
   Supervised Learning Algorithms
3. Gradient Descent
   Loss Functions (recommended)
4. Activation Functions (recommended)
   Neural Network Basics
5. Backpropagation
6. Convolutional Neural Networks (recommended)Transformers & Attention (recommended)
   Deep Learning Architectures
7. The Training Workflow
   Regularization Techniques (recommended)

Keep learning — keep building.