Tech Journal

Testing and Validating The only way to know how well a model will generalise to new cases is to actually try it out on new cases. One way to do that is to put your model in production and monitor how well it performs. This works well, but if your model is horribly bad, your users will complain–not the best idea. ... Read More

This notebook is an exercise in the Pandas course. You can reference the tutorial at this link. Introduction The first step in most data analytics projects is reading the data file. In this exercise, you’ll create Series and DataFrame objects, both by hand and by reading data files. Run the code cell below to ... Read More

📌 Phase 1.4 - Develop Frontend UI to Display Enhanced Insights & Predictions 1. Objectives ✅ Goal Build an intuitive, responsive React-based UI to visualise enhanced API insights and predictions for informed user decision-making. 🎯 Key Tasks Design Insight Visualisation Components: Create interactive cha... Read More

Main Challenges of Machine Learning In short, since your main task is to select a model and train it on some data, the two things that can go wrong are “bad model” and “bad data”. Let’s start with examples of bad data. Insufficient Quantity of Training Data For a toddler to learn what an apple is, all it takes i... Read More

This notebook is an exercise in the Introduction to Machine Learning course. You can reference the tutorial at this link. Introduction In this exercise, you will create and submit predictions for a Kaggle competition. You can then improve your model (e.g. by adding features) to apply what you’ve learned and mov... Read More