Data Science
605 learners
Training Your First Machine Learning Model from Scratch
This course delves into the foundational steps required to build and train a linear regression model from scratch using scikit-learn. You will understand the basics of model training, evaluation, and prediction.
Numpy
Pandas
Python
Scikit-learn
See path
5 lessons
21 practices
3 hours
Badge for Machine Learning and Predictive Modeling,
Machine Learning and Predictive Modeling
Lessons and practices
Lesson 1: Introduction to Machine Learning
House Area and Price Relationship
Enhance Data Visualization by Changing Sample Size
Complete the Data Generation and Visualization
Lesson 2: Training a Linear Regression Model
Training the Linear Regression Model
Adjust Base Price and Price per Square Foot
Predicting House Prices with Linear Regression
Training a Linear Regression Model from Scratch
Train Your Linear Regression Model
Lesson 3: Making Predictions and Visualizing Results
Predicting and Visualizing House Prices
Visualize Predicted Prices Using Line Plot
Predict House Prices
Debugging House Price Predictions
Making Predictions from Scratch
Lesson 4: Evaluating Your Model's Performance
Evaluating House Price Predictions
Removing Noise from Synthetic Data
Predict House Prices and Calculate MSE
Calculating and Comparing Mean Squared Error (MSE)
Lesson 5: Applying Linear Regression to the Real Dataset
Predicting California House Prices
Modifying Feature Selection to Evaluate MSE
California Housing Model Debugging
Preparing Data and Making Predictions
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