ctloo1983team,github

aws-machine-learning-foundations-scholarship

Udacity AWS ML Foundations Scholarship Course Walkthrough

berkeley-jupyter-notebook

Jupyter Notebook tips and tricks for the Berkeley Institute for Data Science lecture. http://bids.berkeley.edu/

car-price-prediction-using-machine-learning-with-python

This dataset contains information about used cars listed on www.cardekho.com This data can be used for a lot of purposes such as price prediction to exemplify the use of linear regression in Machine Learning. The columns in the given dataset is as follows: Car_Name Year Selling_Price Present_Price Kms_Driven Fuel_Type Seller_Type Transmission Owner. This project is about Car Price Prediction using Machine Learning with Python. This is a Regression Machine Learning Project. This is one of the important Machine Learning Projects.

complete-feature-selection

deep-learning-illustrated

Deep Learning Illustrated (2020)

dsp

Metis Data Science Bootcamp - Official Prework Repository

ggd-poirot

Tutorials to help students complete the Metis/DG data project #belgianjamesbond

github_upload

IOD Training Lab

heart-disease-prediction-using-machine-learning-with-python

This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The "goal" field refers to the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4. Content Attribute Information: age sex chest pain type (4 values) resting blood pressure serum cholestoral in mg/dl fasting blood sugar > 120 mg/dl resting electrocardiographic results (values 0,1,2) maximum heart rate achieved exercise induced angina oldpeak = ST depression induced by exercise relative to rest the slope of the peak exercise ST segment number of major vessels (0-3) colored by flourosopy thal: 3 = normal; 6 = fixed defect; 7 = reversable defect The names and social security numbers of the patients were recently removed from the database, replaced with dummy values. One file has been "processed", that one containing the Cleveland database. All four unprocessed files also exist in this directory. To see Test Costs (donated by Peter Turney), please see the folder "Costs" Acknowledgements Creators: Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D. University Hospital, Zurich, Switzerland: William Steinbrunn, M.D. University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D. V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D. Donor: David W. Aha (aha '@' ics.uci.edu) (714) 856-8779 Inspiration Experiments with the Cleveland database have concentrated on simply attempting to distinguish presence (values 1,2,3,4) from absence (value 0). See if you can find any other trends in heart data to predict certain cardiovascular events or find any clear indications of heart health.