Data Preparation: Web Scraping html tables with rvest

Accessing different data sources Sometimes, the data you need is available on the web. Accessing those will ease your life as a data scientist. I want to perform an exploratory data analysis on 2018/19 Season of England Premier league. Are there changes in team performances during the season timeline? Does some teams cluster? Which is the earliest week we can predict team’s final positions? I need the standings table for each week of the season and integrate them in a way that will allow me to plot the graphs that I want.

Why not everyone who smokes develop cancer or who eats a lot develop fatty liver disease? Predicting diseases with machine learning

We are much better at handling diseases than 30 years ago. For example cancer survival rates are much higher now. The significant portion of this increase can be attributed directly to our ability to detect and diagnose cancer earlier. Also, use of insulin and other drugs to control blood glucose in diabetic patients reduced the risk of developing coronary diseases. We are at constant hunt for finding new evidence which environmental factors put us at risk for which diseases.

Start blogging in 5 minutes on Netlify with Hugo and blogdown (September 2019 Update)

This guide will help you to get your website online in a few minutes. Then, customize and add your own material in RStudio environment, push it to your Github repository and benefit from the continuous deployment feature of Netlify. It took me many days of work, reading tens of blog posts, YouTube videos and a lot of testing to figure out all of this. Here is an up to date workflow of how I created my Blog on Github and deployed at Netlify.