Intro to deep learning

Deep learning is different from ML.

Neural network is building block of DL. What is neural network?

Mathematics plays important role in DL.

It has layers like input layer, hidden layer and output layers. Simple neural network has single hidden layer, deep learning neural network has many hidden layers.

Four important components, which are building blocks of nay DL framework

1. Optimizer - The major goal is to keep the cost function as slow as possible. Algorithms like gradient descent perform it and many more. Objective is to minimize coft fuc.
2. Loss - ANy newural n/w it performs a func. regression or classification or any other task. There is some kind of error which is being there, one we can calculate is how much error our model is making. A func is required to catch how much error loss func is making.
3. Metrics - It is very imp to have evaluation criteria, to evaluate how well it is performing.
4. Activation Functions - Most of the machine learning models. It introduces non linearty to your model.