Contains examples of machine learning with Python
Some very basic examples in machine learning. Have included un-common examples (other than the iris dataset). Have attempted to create algorithms examples for varied datasets:
Supervised Learning Projects
ML problem: Predict Animal Type (Mammal/Bird etc) based on Features Algorithms: Decission Trees, Gaussian Algorithm, Regressions, random forests Data: Zoo Dataset, Boston Housing Dataset Technologies: pandas, python, sklearn
Drivers Fleet Data Analysis for Unsupervised Learning
ML problem: Determine clusters from the drivers-fleet data and plot Algorithms: KMeans, Hierarchical Algorithm, DBScan Data: delivery fleet driver data [https://www.nrel.gov/] Technologies: pandas, python, sklearn
Dimensional Reduction implemented for IRIS Dataset
Twitter stream
ML problem: Location based sentiment analysis of #NipahVirus Algorithms: sentiment analysis with Data visualization Data: Twitter API, Live Stream Technologies: tweepy, nltk, pandas, python, sklearn
Stock price prediction
A time series prediction of gold stocks, so traders or bots can gamble based on these predictions. ML problem: time series prediction Algorithms: ARIMA, regression Technologies: sklearn Data: Quandl