Build ML Models From Scratch (Supervised and Unsupervised).
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Updated
May 17, 2023 - Python
Build ML Models From Scratch (Supervised and Unsupervised).
We're going to classify and predict the "Stage" value, which is either Won or Lost, of a dataset containing auction records, using scikit-learn’s library and algorithms such as decision trees, random forests, naïve Bayes, and KNN.
Implementation from scratch for several classification algorithms such as NN, AdaBoosting, KNN and Naive Bayes
CS4391 Computer Vision Final Project
Application of different ML classification algorithms
Classification of Cardiovascular Disorders using machine learning, Data Analysis of NHANES dataset and Visualizaiong the results
K-Nearest Neighbors algorithm for classification and regression implemented from scratch
A binary classification machine learning mode (developed without the use of pre-existing machine learning frameworks) that implements logistic regression to predict whether a given image is a monkey or a gorilla
This repo uses Deep Learning (DL) model to classify disease in Cassava plants.
Data Science Project
A convolutional neural network to classify the CIFAR-10 image dataset.
The MNIST classification model using the LeNet network with Tensorflow and Keras
Scratch implementation of machine learning algorithms on tensorflow.
Machine Learning training algorithms and implementations
Project for UCD Physics 250 (Econophysics) - Predicts whether a group of songs on the Billboard Top 100 list will stay on the list the next week.
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