Some common module used in deep learning and machine learning

This is our Final Project for our Big Data Class in Second Semister in Lambton College. In this project we learn about Nural Network and see how the change in the Number of Nurons and learning rate effects rate of learning.

Two case studies: effects of changing the learning rate on model perfomance for image classificaiton, and cardiac failure prediction using clinical data

We built an optimization technique that, at each learning step, automatically learns which best learning rate to use for gradient descent.

TensorFlow/Keras implementation of the paper: 'Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates'

TVLARS - A Fast Convergence Optimizer for Large Batch Training

The main aim of this project is to built a predictive model using G Store data to predict the TOTAL REVENUE per customer that helps in better use of marketing budget.

This project involves training a machine learning model and plotting its learning curves to analyze training and testing accuracies, utilizing Java for model execution and Python for data visualization. It includes commands for compiling and running the Java program, generating plots, and sending results via email.

A method for assigning separate learning rate schedulers to different parameters group in a model.

This repository focuses on the Neural Networks and deep learning. It is a workbook you can refer it for a reference. I'll Include following content here: Neurons, perceptrons, weight and biases, learning rate, activation form, hyper parameters, RNN, CNN and other popular concepts.

Investigating Gradient Descent behavior in linear regression

This program implements linear regression from scratch using the gradient descent algorithm in Python. It predicts car prices based on selected features and uses a dataset of cars with their respective prices.

Convenience classes/functions for common machine learning tasks

Reproduction of the "Don't Decay the Learning Rate, Increase the Batch Size" conference paper.

Building Deep Neural Network for Google Street View Dataset

Interactive Learning Rate Scheduler for PyTorch

callbacks in ai

Neural net solver with auto-tuned hyperparameters (Python 3.5)