Machine Learning Zoomcamp Week 2

This is week 2 of #mlzoomcamp and it was all about Linear Regression.

You can view this weeks homework

The goal of this homework was to create a regression model for predicting the car fuel efficiency (column 'fuel_efficiency_mpg') and I did that in the following steps: 1️⃣ EDA and preparing the dataset by splitting it into training, validation and testing set. 2️⃣ Shuffling and normalizing the data by applying log transformation. 3️⃣ Building a linear regression from scratch using Numpy. 4️⃣ Evaluating a model on a validation set by using the Root Mean Squared Error (RMSE). 5️⃣ Making predictions with the model.

The focus of the lessons for this week was learning how to perform Linear Regression from scratch, without using any machine learning library, and it was great to know how the 🚗 Case study: Car price prediction 🤖 Data Cleaning & Exploration 🧮 Linear Regression 🔄 Root Mean Squared Error 🐍 Feature Engineering 📚 Regularization 📊 Model training and using the model and others.