In this project, I used different techniques, such as correlation and Fisher test to identify important parameters affecting survival rates. After cleaning the data for the years 2011-2015 from SEER, I applied methods like Random Forest, Logistic Regression, and Deep Neural Networks to estimate the survival rate in breast cancer with 94% accuracy, using only 16 indicators from SEER

SEER DB for Breast Cancer Survival rate estimate with RandomForest, Logistic Regression, and Deep Neural Network.

Use SEER database between 2011-2015 to predict the survival rate of Breast Cancer patients using RF, RL, GBM, and DNN.

This is SPAM/HAM e-mail classification project using Naive Bayes (NB), SVM, Deep Learning, and Random Forest

Recommender Algorithms - Goodreads Analyses

Hi, This is the 1st and introductory submission for the DATA606 project. Best. -Koohyar

Sentiment Analyses Assignment, working with tidytext and additional sentiment analyses.

This is DATA607 final project submission with the latest update, conclusion, and summary.

This is 3RD project team work for DATA607

Working with NYTimes APIs.

Loading XLM, HTML, and JSON to RStudio and compare them with original file. K00hPy

Data tidying, cleanup, and transformation.

Hi, This is the 5th-week assignment for DATA607 regarding tidying and data transformation. We used dplyr and tidyr to manipulate data and work with it.

Hi, This is Lab3 submission for DATA606. Thanks!

Hi, This is a submission for Extra Credit 2 for Elo chase rating system. Best.

This is the 1st project for DATA607, written and presented by Koohyar P.

Hi, DATA606 LAB2 assignment. working with nycflights database and learning how to use ggplot and summarize statistics. -Koohyar

This is the extra credit for DATA607

This is the 3rd assignment for the DATA607 for text manipulation.

Hi,This is DATA607 2nd Assignment working with SQL

This is Koohyar's submission for DATA606 LAB1

This is a Test