Python

Regression: Fit a Line with Gradient Descent

Fit a line to real data by building gradient descent yourself with numpy, nudging slope and intercept downhill step by step until the line actually predicts.

PythonIntermediatePortfolio piece

What you'll be able to build

Fit a line to real data by building gradient descent yourself with numpy, nudging slope and intercept downhill step by step until the line actually predicts. Along the way you pick up real, transferable Python skills, not just this one project:

  • numpy arrays and vectorized arithmetic
  • the mean-squared-error loss function
  • computing gradients by hand
  • the gradient-descent update loop
  • tracking loss to confirm convergence
  • using the fitted line to predict new values

A course like this one

Yours is built from your own placement, so module count and depth will differ. This map shows what a intermediate-level Python learner building Regression actually gets.

  1. Module 1: Values and output5 lessons

    Builds the script for your Regression.

  2. Module 2: Collections and data5 lessons

    Builds the data flow workflow for your Regression.

  3. Module 3: Branching and state5 lessons

    Builds the function that powers your Regression.

  4. Module 4: Functions and tests5 lessons

    Builds the reusable module for your Regression.

  5. Module 5: Files, APIs, and persistence5 lessons

    Builds the service boundary for your Regression.

  6. Module 6: Packaging and review3 lessons

    Builds the release package for your Regression.

How the lessons actually work

Leans on:numpy

Every lesson has you predict what a piece of Python code will output before you run it, then run it for real in your browser and fix what you got wrong. Each module ends in a challenge gate with hidden tests, so you can't advance until your code actually works. The course closes with a capstone that assembles everything into Regression, and a runnable proof page tied to your own code.

Common questions

How long does the Regression: Fit a Line with Gradient Descent course take?

about 7 hours, across 6 modules and 28 lessons, at roughly 15 minutes per lesson. Your own course may run shorter or longer, since it's sized to your placement result, not a fixed template.

Do I need experience?

Some. This is an intermediate-tier Python project, so it assumes you're comfortable with Python basics and pushes past them.

How much does it cost?

$15 one-time, no subscription. The first module is free, so you can see exactly how the course teaches before you pay for the rest.

No subscription. Module one is free.

Build my Regression