This repo is tutorial for exploring various algorithms for Multi-output prediction in ML and DL using a regressor data and understanding them how mathematically they work.

I have explored: Machine learning algorithms

• for which the multi-output available as default:

1. Linear regression
2. KNN Regressor
3. Decision Tree Regressor.
4. Random forest.

• Also, Explored methods that can be used with Algorithms which doesn't support multi-output

1. Chain
2. Direct using SVM

Deep learning algorithms:

1. Simple Feed-forward Neural network