The Ruby DataMining Gem, is a little collection of several Data-Mining-Algorithms
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Updated
Jul 24, 2015 - Ruby
The Ruby DataMining Gem, is a little collection of several Data-Mining-Algorithms
K-Nearest Neighbors Classifier
Identifying the conspirators in Enron fraud using Email Data
The fraud identification models were build using Python Scikit-learn machine-learning module.
Implementation of Neural Network from scratch
A practical application in e-commerce applications to infer sentiment (or polarity) from free-form review text submitted for a range of products. I have wrote a K Nearest Neighbor algorithm to calculate the locality of a review vector in the Euclidean space using the Cosine Similarity Metric.
Identifying Image Orientation using Supervised Machine Learning Models of k-Nearest Neighbors, Adaboost and Multi-Layer Feed-Forward Neural Network trained using Back-Propagation Learning Algorithm
Classification of images based on their orientation using Neural Networks, Adaboost and K-Nearest Neighbors
This repository is for managing all my assignment for Artificial Intelligence Course
CSE 575 Statistical Machine Learning
A python script that classifies iris flower species based on their various dimensions.
Python ML/AI repository
Automatic method for the recognition of hand gestures for the categorization of vowels and numbers in Colombian sign language based on Neural Networks (Perceptrons), Support Vector Machine and K-Nearest Neighbor for classifier /// Método automático para el reconocimiento de gestos de mano para la categorización de vocales y números en lenguaje d…
python implementation of mmachine learning of different classifiers and their comparison
These Codes are written as part of Neural Networks and Deep learning course at UCLA.
My "Hello, World!" program in machine learning.
An implementation of the K-Nearest Neighbors algorithm from scratch using the Python programming language.
This is a classification of iris flower using k nearest neighbour classifier
K-NEAREST NEIGHBOR and HyperParameter Optimization using GridSearch.
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