This blog will demonstrate a simple way to frame financial stock data into a sequence classification problem. The business case is to, given historical stock data, create a model that will predict whether a trade(action) will be ‘Positive’ or ‘Negative.’ I can turn the business case into an ML problem…

For this blog, I will import a CSV file to a MySQL server(using MAMP) to create a practice platform for SQL statements. More specifically, I will import the titanic dataset(train.csv), which I can find here (https://www.kaggle.com/c/titanic). This tutorial will be broken down into three steps: Installing MAMP Installing and editing configuration…

Pearson’s chi-squared test for independence is used to test whether there is an association between categorical variables by seeing if there is a statistical difference between the expected counts against the observed. The test uses the aggregated counts of the categorical variables that summarize the data into a table called…

Agile is an approach to project management that aims always to have a working product while continuously improving in short increments. Instead of delivering a product in the end, as in the case for Waterfall, Agile looks to provide a minimum viable product(MVP) and improve on it iteratively based on…

On March 21, 2021, a massive container ship, Ever Given, was found stuck in the Suez Canal. The Suez Canal is an important trade route as it connects a water path between Europe and Asia without going around Africa. The ship blocked the pathway for six days delaying hundreds of…

For this blog, I will demonstrate three techniques to handle class imbalance using NYS PUMS(Public Use Microdata Sample) Census data. (You can find the dataset here.) Training classification models with imbalanced classes can lead to the model biasedly predicting the majority class. Class Imbalance Undersampling Oversampling SMOTE-NC A pseudo-objective is to classify…

For this blog, I will run a hypothesis test if the population count around a well affects its functionality. I will be using the dataset from the Tanzania Water Pump Challenge hosted by Data-Driven and the WorldPop population estimations to feature engineer population estimations in a 1km, 5km, and 10km…

Regularization in gradient boosted regression trees are applied to the leaf values and not the feature coefficients like in lasso/ridge regression. For this blog, I will break down the explanation into three steps: Lasso & Ridge Regression - A brief re-cap of lasso and ridge regression Gradient Boosted Regression Trees …

I recently came across an interesting problem that required some understanding of Absorbing Markov Chains. The objective to calculate the percentages(in the long run) of ending states given an initial state. The input is a frequency table where each state has counts of transitions based on its index. To elaborate…