Work on Bayesian growth mixture models including hidden Markov chains and softmax regressions for representing latent class memberships.

Analyze, visualize and predict customer churn using Machine Learning

This project has a comprehensive exploration of two key topics: Softmax Regression and Contrastive Representation Learning. The dataset used for this project is the CIFAR-10 dataset, which can be accessed by link given below

This project utilizes neural networks to recognize handwritten digits (0-9) through multiclass classification, employing ReLU activation and Softmax function for accurate predictions.

Statistical Pattern Recognition (classic machine learning)

Deep Learning basics in Python using NumPy, PyTorch, and TensorFlow/Keras: linear regression, softmax regression, multilayer perceptron, etc.

This repository is a compilation of machine learning algorithms implemented by me on differnet datasets and I'm currently working on it. The algorithms are categorized based on the types of data they are designed to handle and some of the codes are just a basic descriptions about the algorithms.

Machine learning algorithms in Dart programming language

Contains Optional Labs and Solutions of Programming Assignment for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2023) by Prof. Andrew NG

A model to classify images of handwritten digits using Multiclass Logistic Regression

Applied Machine Learning (COMP 551) Project

A list of machine leaarning tasks carried out in a set of series spread across 3 Colab Notebooks

Deep learning methods for sentiment analysis classification of covid-19 vaccination tweets

电子科技大学 2020 级《统计学习与模式识别》课程代码。

Machine Learning Model to predict student graduation grade

Projects for Knowledge Engineering class (BIT北理工, NLP, 知识工程)

[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

Softmax Regression applied to MNIST Handwritten Dataset