Learning about Perceptron and Multi layered perceptron
Learning various types of algorithm like forward and backward propagation in neural networks without using the library and implementing all form the scratch without use of any inbuilt library understanding maths behind all the deep concepts and using visualise visualising the surface build by our neural network on various datasets like circles moons and xor data set and checking the accuracy for every data set. visualising the decrease in loss
we are provided with two features and we have to classify it in class 1 or 0. Two files are provided to you train and test.
Train: It consist of two files Xtrain containing the features and Ytrain containing labels associated with them. Test: It also consists of two files Xtest which contains the features on which your model will be tested and sample output which defines the format in which your output needs to be submitted.