Neural Networks from Scratch-MNIST
manzoor bin mahmood
Bengaluru, Karnataka
- 0 Collaborators
In-depth implementation of neural network with minimum use of libraries ...learn more
Project status: Published/In Market
Groups
Student Developers for AI,
DeepLearning,
Artificial Intelligence India,
Starting From Scratch,
Intel AI DevCamps,
Intel Deep Learning Group
Intel Technologies
Intel Integrated Graphics
Overview / Usage
In this project neural network has been implemented from basics without use of any framework like TensorFlow or sci-kit-learn. Training has been done on the MNIST dataset. Implementation has been done with minimum use of libraries to get a better understanding of the concept and working on neural nets.
It gives a clear understanding of neural networks and can be used for research work by manipulating the network.
Methodology / Approach
The following methodology was adopted:
- Functions for random initialization of weights and bias
- Activation functions
- Derivatives of the activation function
- Function for Forwarding propagation
- Backward propagation
- The cost has been written separately and derivative has been found.
Technologies Used
Software used:
- Python
- Jupyter Notebook
Intel
- Intel Integrated Graphics
Tools
- Numpy-For array manipulations
- Matplotlib-For visualization
Repository
https://github.com/manzoormahmood/mnist_neural-network-from-scaratch