marcotav/supervised-machine-learning

This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using Lasso and Ridge regressions.

## Supervised Machine Learning Projects       [](https://opensource.org/licenses/MIT) Notebooks and descriptions • Contact Information ### Notebooks and descriptions | Notebook | Brief Description | |--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------| |[predicting-comments-on-reddit](http://nbviewer.jupyter.org/github/marcotav/deep-learning/blob/master/painters-identification/notebooks/capstone-models-final-model-building.ipynb) | In this project I determine which characteristics of a post on Reddit contribute most to the overall interaction as measured by number of comments.| |[tennis-matches-prediction](http://nbviewer.jupyter.org/github/marcotav/deep-learning/blob/master/bitcoin/notebooks/deep-learning-LSTM-bitcoins.ipynb) | The goal of the project is to predict the probability that the higher-ranked player will win a tennis match. I will call that a `win`(as opposed to an upset).| |[churn-analysis](http://nbviewer.jupyter.org/github/marcotav/deep-learning/blob/master/keras-tf-tutorial/notebooks/neural-nets-digits-mnist.ipynb) | This project was done in col