This is an example of a Decision Tree model (very useful and popular method) to make prediction using the power of Machine Learning…using just a normal PC. Here we predict salary (depedendent variable) by giving various types of criteria (different forks in a decision tree). e.g. What’s the salary of a particular gender, of some […]

# Blog

## Derivatives? Why?! Can I code it?

Derivatives are used to find the rate of changes of a quantity with respect to another quantity. The derivative of a variable tells us the rate of change of a function’s output value as it varies from the initial value…how much is it changing? For a straight line (e.g. linear regression), we can calculate the […]

## Wanna be a weather reporter? Me neither! So let’s do Machine Learning (AI)! Part 2/2

This is a continuation of weather prediction via ML and is the final part (2/2) where I demonstrate how to write Python code to leverage a neural network algorithm called Neural Prophet, a quite straight-forward and useful model. Be sure to read the first part that focuses on understanding the data in Excel and some […]

## Wanna be a weather reporter? Me neither! So let’s do Machine Learning (AI)! Part 1/2

Reporting weather by reading off the predictions is obviously a very different skill than creating the code and models that actually predicts the weather! Not just forecasting for the next 5 days, but actually PREDICTING for any number of period in the future! Is that even possible? Yes, it is albeit there are myriad of […]

## Logistic Regression Example (Excel, Python)

In my previous blog on Sigmoid function, I touched on its usefulness and how it’s used to solve Logistic Regression problems either in binary or multiclass classification scenarios. Be sure to check that out http://flyingsalmon.net/?p=3879 first! In this blog, we’ll be using a dataset containing people’s ages and whether or not they bought life insurance […]

## What is Sigmoid function and why?

In this blog, I touch on a core function that’s used in many machine learning scenarios whether explicitly or as a part solving a given problem. This is extremely useful for recoding values for classification (binary or multiclass) where we need to map some categorical values into a finite range of values (e.g. 0 or […]

## Bill Gate’s first resume (made public)

Recently, I came across Bill Gates’ first resume from circa 1974 in a Microsoft almni discussions forum. It’s very interesting to see how it was customary to put in the candidate’s number of dependents/children, height, and weight even though it was for a white-collar job. I also find the innocence of some phrases used by […]

## Creating music and teaching coding

Have you heard of Earsketch? It’s an amazing, fun way to create music while learning, practicing, teaching coding! Yes, music and coding all in one with its online, free platform (for students)…you just need a browser. It supports Python and Javascript coding in their online editor and you can compile and run the code on […]

## Machine Learning (Prediction with Dummy Variables)

I already shared ways to leverage Python for Machine Learning and predict values in univariate and multivariate regression models. Be sure to read those before proceeding to this as this builds on those concepts. In this post, we’ll also make prediction using regression model but this time we have categorical values to deal with. Categorical […]

## Machine Learning In Python (Multivariate Linear Regression)

In my previous post, I shared how to predict using a single criteria leveraging machine learning in Python. If you haven’t read that, be sure to read that first here to get a better understanding of what we’re trying to do. In this post, I’ll let computer predict something based on multiple criteria. For example, […]