This repository consists of standard Machine Learning Algorithms
It includes the use of standard libraries scikit_learn, pandas, tensorflow, quandl
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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
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Movie Recommender system using dataset of LightFM and predicting top 3 movies and comparing with actual top 3