GitHub - e2skm/Machine-Learning: This is repository is for my machine learning projects. It contains datasets and Jupyter notebook files. My aim is to cover common algorithms for the three types of Machine Learning. So Far I have covered Supervised and Unsupervised learning. I am currently working on adding Reinforcement Learning algorithms.

Name		Name	Last commit message	Last commit date
Canada_per_capita_income.csv		Canada_per_capita_income.csv
Data Science from scratch - First Principles with python1.ipynb		Data Science from scratch - First Principles with python1.ipynb
Head sizes and Brain weights of human beings - ML project2.ipynb		Head sizes and Brain weights of human beings - ML project2.ipynb
Iris project - The Hello World of Machine Learning.ipynb		Iris project - The Hello World of Machine Learning.ipynb
K-means clustering - 5000 movies dataset - ML project10.ipynb		K-means clustering - 5000 movies dataset - ML project10.ipynb
KNN - Iris dataset- ML project6.ipynb		KNN - Iris dataset- ML project6.ipynb
Linear Regression - Canada annual IPC dataset - ML project9.ipynb		Linear Regression - Canada annual IPC dataset - ML project9.ipynb
Logistic Regression - SUV dataset - ML project4.ipynb		Logistic Regression - SUV dataset - ML project4.ipynb
Logistic Regression -Titanic dataset - ML project3.ipynb		Logistic Regression -Titanic dataset - ML project3.ipynb
Naive Bayes classifier with Scikit learn - PIMA India dataset - ML project8.ipynb		Naive Bayes classifier with Scikit learn - PIMA India dataset - ML project8.ipynb
Predict Student dropout using ML- PersonalML project1.ipynb		Predict Student dropout using ML- PersonalML project1.ipynb
Q-Learning implementation with NumPy.ipynb		Q-Learning implementation with NumPy.ipynb
Red wine quality - PersonalML project2.ipynb		Red wine quality - PersonalML project2.ipynb
StudentDropout.csv		StudentDropout.csv
Three types of Naive Bayes classifier with Scikit learn - Iris dataset - ML project8.ipynb		Three types of Naive Bayes classifier with Scikit learn - Iris dataset - ML project8.ipynb
Titanic-Dataset.csv		Titanic-Dataset.csv
White wine quality - PersonalML project3.ipynb		White wine quality - PersonalML project3.ipynb
diabetes.csv		diabetes.csv
headbrain.csv		headbrain.csv
iris.data		iris.data
movie_metadata.csv		movie_metadata.csv
suv_data.csv		suv_data.csv
winequality-red.csv		winequality-red.csv
winequality-white.csv		winequality-white.csv

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This is repository is for my machine learning projects. It contains datasets and Jupyter notebook files. My aim is to cover common algorithms for the three types of Machine Learning. So Far I have covered Supervised and Unsupervised learning. I am currently working on adding Reinforcement Learning algorithms.

aritificial-intelligence data-science machine-learning-algorithms statistics-and-probability

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