A python notebook

This repository contains an ipython notebook which implements an Artificial Neural Network using keras to do churn prediction .

This repository contains mini projects in deep learning with Jupiter notebook files. For each ANN CNN RNN

Notebook containing BP and PPG signal processing and ANN utilization for determining BP from PPG signals.

Implementation of Artificial Neural Network from Scratch using Python and Jupyter Notebook

Implementing an ANN using PyTorch (under 800,000 parameters) to achieve +92% accuracy in under 100 epochs.

Welcome to the Deep Learning Repository! This repository serves as a comprehensive collection of Jupyter notebooks, exploring various deep learning concepts and applications. Whether you are a beginner or an experienced deep learning enthusiast, this repository offers a wide range of practical exercises, models, and predictions.

Jupyter notebook for the "10-year Coronary Heart Disease (CHD) risk from the Framingham Heart study dataset" project (part of the course in Machine Learning)

This Notebook kernel deals with a dataset from 2017 of three 3 MW windturbines. It covers an EDA and Data Visualization of the Turbine and and the comparison of different regression Models including Decision Tree, Random Forrest, Support Vector Machine and ANN.

Developed using Python and Google Collab Notebook, this project leverages a Simple Multilayer Perceptron Neural Network (Feed Forward model) for breast cancer prediction. It utilizes the sklearn library for , and model evaluation. The dataset used is the Breast Cancer Wisconsin (Diagnostic) Data Set, Accuracy-95%