Deep Learning Basics

Basics Deep Learning Program
In this Repository I will add Basics program for Deep Learning which are built from scratch using basic Python Libary

Content:

1. Vector Operation
2. McCulloch-Pitts Neuron Model
3. Single Layer Perceptron
4. Sigmoid Neuron
5. Feed Forward Neural Network for Multiclass classification
6. BackPropagation In Neral Network
7. Implementing Vectorization over Neural Network for better performance
8. Learning Algorithm Optimization
9. Differnt Optimization Algorithm Comparison
10. Different Activation function and Initialization Methods
11. Different Regularization technique to solve overfitting

Prequest:

1. Basic Python
2. Numpy
3. Pandas
4. Matplotlib
5. Scikit-Learn
6. Vector Algebra
7. Linear Algebra
8. Calculas

Datasets:

1. MobileCleaned.csv
2. IRIS.csv
3. data.csv

If any notebooks does not opens, then please go to nbviewer.jupyter.org/ and paste the link of the notebook.