This project was developed during the course:

Linear Regression With Python

by Coursera Project Network

The hands on project on Linear Regression with Python is divided into following tasks:

Task 1: Introduction

• Introduction to the problem

• Introduction to the Rhyme interface

Task 2: Dataset

• Refresher on linear regression

• Create a function to synthesize data

Task 3: Initialize Parameters

• Continue the refresher on linear regression

• Start writing the linear model class

Task 4: Forward Pass

• Refresher on gradient descent

• Implement the forward pass

Task 5: Compute Loss

• Extend the linear model and add a function to compute loss

Task 6: Backward Pass

• Implement a backward pass function

• Calculate gradients dW and db

Task 7: Update Parameters

• Update the parameter values with gradients obtained with backward pass

Task 8: Training Loop

• Implement the final training loop

• Train the model

Task 9: Predictions

• Get predictions from the trained model

• Get predictions from an untrained model for comparison

Tecnologias utilizadas

Instructor: Amit Yadav - Machine Learning and Data Science instructors at Rhyme