Data Science:Hands-on Diabetes Prediction with Pyspark MLlib

Would you like to build, train, test and evaluate a machine learning model that is able to detect diabetes using logistic regression?

This is a Hands–on Machine Learning Course where you will practice alongside the classes. The dataset will be provided to you during the lectures. We highly recommend that for the best learning experience, you practice alongside the lectures.

You will learn more in this one hour of Practice than hundreds of hours of unnecessary theoretical lectures.

Learn the most important aspect of Spark Machine learning (Spark MLlib) :

Pyspark fundamentals and implementing spark machine learning

Importing and Working with Datasets

Process data using a Machine Learning model using spark MLlib

Build and train Logistic regression model

Test and analyze the model

The entire course has been divided into tasks. Each task has been very carefully created and designed to give you the best learning experience. In this hands–on project, we will complete the following tasks:

Task 1: Project overview

Task 2: Intro to Colab environment & install dependencies to run spark on Colab

Task 3: Clone & explore the diabetes dataset

Task 4: Data Cleaning

Task 5: Correlation & feature selection

Task 6: Build and train Logistic Regression Model using Spark MLlib