Internship← Artificial Intelligence & Machine Learning learning pathArtificial Intelligence & Machine Learning · Module 8 of 10
Neural networks and deep learning
Learn complex patterns with neural networks.
📖 Key ideas
- Neurons compute weighted sums and activations.
- Networks learn via backpropagation and gradient descent.
- CNNs for images; RNNs/Transformers for sequences.
- Frameworks: TensorFlow/Keras, PyTorch.
- Needs more data and compute (GPUs).
💡 Real-life example: A neural network is a team of tiny decision makers passing notes until a final answer emerges.
NeuronUnit computing weighted sum + activation
BackpropagationComputing gradients
CNNConvolutional neural network
TransformerAttention-based architecture