Sometimes the data we need to evaluate is unorganized, and by this I mean the data is missing target values. Target values are the values we are trying to predict. When this happens we need a way to group the data into defining clusters; pictures of ...

Sometimes there is a lot of 'noise' in the data. By noise I mean data that is not relevant to the target variable. There are methods to determine the impact of each column to the outcome variable, and then selecting only the the columns that are of h...

My poor dad suffers from ckd, maybe performing data analysis on ckd data will allow me to give him some comfort behind the reason for his poor appetite. University of California, Irvine UCI has some data on ckd patients, this data contains biomarkers...

These two terms overfitting and underfitting relate to situations in a machine learning algorithm, specifically in classification algorithms. For example, how to classify a guy being attractive or not attractive. You can use different features to hel...

In the React Native world we pretty much only worry about calling an endpoint and receiving some data from such endpoint. We are usually blind to all the work that happens in retrieving this data. In this post I am going to trace the api call from wh...

A few things come to mind after spending almost 24 hours working on this problem. When swapping elements in a linked list always follow these steps: Swapping distant from each other 1. Update the values around the nodes first 2. Update the next poi...

I was a React Native Engineer a few times, I made a few modules that communicated with native code which I thought was the pinnacle of my React Native career, made different schemes, added push notifications, among other things. Things shifted after ...