Simple neural network built with numpy to see classification metrics.
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Updated
Feb 23, 2020 - Jupyter Notebook
Simple neural network built with numpy to see classification metrics.
A feed-forward-only neural network library, planned for embedded devices
A tool that quickly and accurately segments Urdu sentences and words in your text.
This repository contains the solutions of Coursera course Intro to Deep Learning Solutions
Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.
Realized forward propagation of Neural Network using C language
Logistic Regression and Neural Networks implementation from scratch
A simple perceptron based artificial neural network using python and numpy package only.
This notebook demonstrates a neural network implementation using NumPy, without TensorFlow or PyTorch. Trained on the MNIST dataset, it features an architecture with input layer (784 neurons), two hidden layers (132 and 40 neurons), and an output layer (10 neurons) with sigmoid activation.
This project involves the development of a digit recognition system using a two-layer neural network, specifically designed to classify handwritten digits (0-9). The system was built and trained on the MNIST dataset, which contains 70,000 images of handwritten digits.
Programming exercises for the Machine learning course offered by Coursera and Andrew Ng
Neural network for letter recognition
Notes & simple python code to aid understanding the workings of neural networks
Solutions for the Coursera Machine Learning Course (Andrew Ng).
To build a multilayer perceptron model and to train datas from it
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