A place to store all my ideas, experiments, and observations of the software engineering landscape.
Learn how Multidimensional Scaling (MDS) and Principal Coordinate Analysis (PCoA) can be used to uncover patterns and relationships in car data. This post explores the similarities and differences between MDS, PCoA, and PCA, and demonstrates their application using a car dataset.
Imagine you have a dataset containing information about various car models, each with multiple features such as horsepower, fuel efficiency, weight, and price. How can you extract meaningful information from this complex data? Enter, Principal Component Analysis!
Exploring regularization techniques, including Ridge (L2) and Lasso (L1) regression, to prevent overfitting and improve model performance. This post covers how regularization works, its application in linear and logistic regression, and the differences between L1 and L2 regularization.
Exploring the importance of coefficients and Wald's test in logistic regression. This post covers how to interpret coefficients, assess feature significance using Wald's test, and determine if a feature is useful for the model.
Exploring logistic regression for binary classification problems. This post covers the fundamentals of logistic regression, the sigmoid function, and the importance of gradient descent in training the model.
Delving into the fundamentals of linear regression, both simple and multiple, using practical examples. This post covers data visualization, model training, prediction, and evaluation.
Starting the journey with the essential first step of any ML project. In this post, we dive into the key data preprocessing steps using a basic dataset, including handling missing data, encoding categorical variables, splitting the dataset, and feature scaling.
In today's blog, we will be discussing the logistic regression model and how it is used in neural networks. I will also be *attempting* to explain some of the maths behind it, although I'm still getting to grips with it myself tbh.
So this week I decided I want to pick up the Deep Learning and AI course on coursera. It turns out there's a reason 700,000 people subscribed to the course, as it has 5 different courses...
In today's blog, I'm going to talk about how much the React ecosystem has changed from 4 years ago when I initially started fiddling around with it with create-react-app, how server-side-rendering has become a big deal, and how Remix uses file based routing to make loading data so easy.
This is my first post on my blog. I'm trying to do something new here and document everything I learn and do for a year. I hope you enjoy it!
