ML-Models

This repository consists of standard Machine Learning Algorithms
It includes the use of standard libraries scikit_learn, pandas, tensorflow, quandl

The Perceptron Model is implementation of a single neuron called Perceptron
It implements basic gates that is OR, NOR, AND and NAND gates
The Linear Regression works on the data of google stocks and using linear regression getting the best fit line
Then predicting the stock prices for next 30 days
The K-Nearest algorithm works on data of breast cancer and classifies them into benign or malignant
One of it using standard library and other one without using standard library
K Means Clustering on Titanic Dataset to predict a person was alive or dead
One of it using standard library and other one without using standard library
Classifier using scikit learn: this implements basic classifier tree.DecisionTreeClassifier() and neural_network.MLPClassifier() to predict, several other classifiers are mentioned as comment in the file
Movie Recommender system using dataset of LightFM and predicting top 3 movies and comparing with actual top 3

Name		Name	Last commit message	Last commit date
Latest commit History 36 Commits
Classifier using sklearn		Classifier using sklearn
Genetic Algorithm using TPOT		Genetic Algorithm using TPOT
K Nearest Neighbours		K Nearest Neighbours
KMeans Clustering		KMeans Clustering
Linear Regression		Linear Regression
Movie Recommender System		Movie Recommender System
Perceptron Model		Perceptron Model
Sentiment Analysis using Tweepy		Sentiment Analysis using Tweepy
Stock Predictor using SVR		Stock Predictor using SVR
README.md		README.md

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