Classified images from CIFAR-10 dataset using different machine learning algorithms including - SVM, neural-networks.
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Updated
May 9, 2017 - Python
Classified images from CIFAR-10 dataset using different machine learning algorithms including - SVM, neural-networks.
There are some basic implementations of K-nearest neighbors and Naive Bayes classifiers.
4 supervised classifiers from Python Machine Learning Chapter 3 by Raschka
Predicting Crowdfunding Success for Classroom Projects on DonorsChoose.org
Implementation of weka k-NN and SVM classifiers in Java
Collection of code covering various topics in Machine Learning
An MPI based implementation of K-NN search algorithm, aimed for use on CPU clusters.
Being able to perform gameplay analysis of NBA players, NBA Predictive Analytics is a basketball coach's new best friend.
Investigated factors that affect the likelihood of charity donations being made based on real census data. Developed a naive classifier to compare testing results to. Trained and tested several supervised machine learning models on preprocessed census data to predict the likelihood of donations. Selected the best model based on accuracy, a modif…
Repository of Artificial Intelligence Course Final Assignment
Assignments and independent projects I completed for Harvey Mudd's CS for Insight.
In this project, we implemented an activity monitoring system for the classification of user activities such as Walking, Sitting, Standing, and Laying down which were captured using a smartwatch provided to us in the course. Various phases were involved in the fulfilment of this project ranging from data collection, data preprocessing, feature e…
Classifier for the iris data set using the k-nearest neighbors algorithm.
Build my own K-nearest-neighbors algorithm and compare the accuracy with KNeighborsClassifier
A project in machine learning based on the completed Netflix competition
K-nearest-neighbors algorithm implementation
k Nearest Neighbors - Predicting car prices basis their automobile specifications.
This is a repository for implementing statistical learning models from scratch using the Python and Java programming languages.
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