JAX compilation of RDDL description files, and a differentiable planner in JAX.

A header-only C++ Library for Optimization Algorithms

XCSF learning classifier system: rule-based online evolutionary machine learning

Dynamically adjusts load balancers coupled with auto scalers in response to workload changes using weakly coupled Markov Decision Processes (MDPs) and a two-timescale online learning approach.

A proof of concept of a recursion doing stochastic gradient descent for a simple neural network. Done in Python3 with numpy

Stanford-CS221 class practical's, Assignments and projects

This project will cover some of the basic Artificial Intelligence along the course using Python. Mainly will use Numpy to build everything. I write all the files in Python and it refers back to the school labs at Dalhousie University.

flexible and extensible implementation of a multithreaded feedforward neural network in Java including popular optimizers, wrapped up in a console user interface

recommender systems algorithms

Parametric estimation of multivariate Hawkes processes with general kernels.

AutoSGM

The ability to predict prices and features affecting the appraisal of property can be a powerful tool in such a cash intensive market for a lessor. Additionally, a predictor that forecasts the number of reviews a specific listing will get may be helpful in examining elements that affect a property's popularity.

A basic neural network with backpropagation programmed from scratch in C++

Logistic Regression with different optimizers in Python from scratch

Easy-to-use linear and non-linear solver

This code uses computational graph and neural network to solve the five-layer traffic demand estimation in Sioux Falls network. It also includes comparison of models and 10 cross-validations.

Gradient Descent is a technique used to fine-tune machine learning algorithms with differentiable loss functions. It's an open-ended mathematical expression, tirelessly calculating the first-order derivative of a loss function and making precise parameter adjustments.

This repository contains my solutions and implementations for assignments assigned during the Machine Learning course.