Solving problem 7.1 from the MIT course “18.06SC – Linear Algebra”.
Solving the problem from the 7. recitation video from the MIT course “18.06SC – Linear Algebra”.
Solving problem 6.3 from the MIT course “18.06SC – Linear Algebra”.
Solving problem 6.2 from the MIT course “18.06SC – Linear Algebra”.
Solving problem 6.1 from the MIT course “18.06SC – Linear Algebra”.
Different datasets have different underlying structures, while some have linear underlying structures other can have nonlinear structures:
Solving the problem from the 6. recitation video from the MIT course “18.06SC – Linear Algebra”.
Linear regression is one of the oldest and most fundamental forms of linear modelling, developed/discovered by none other than Carl Fredriech Gauss. Much of modern machine learning is just a beefed up version of linear regression so its worth understanding it well.
Solving problem 5.3 from the MIT course “18.06SC – Linear Algebra”.
Solving problem 5.2 from the MIT course “18.06SC – Linear Algebra”.