This course teaches Simple Linear Regression and Multiple Linear Regression using Scikit Learn and Spark MLLib. Students will learn to enable Apache Spark (Pyspark) on Jupyter Notebook and Google Colab. The course covers data preprocessing, model building, and evaluation techniques such as MSE, RMSE, and MAE. The intended audience for this course is individuals interested in machine learning, specifically in using Spark for large-scale data processing.
Overview
Syllabus
Simple Linear Regression using Scikit Learn & Spark MLLib | Introduction & Intuition.
Enable Apache Spark(Pyspark) to run on Jupyter Notebook - Part 1 | Install Spark on Jupyter Notebook.
Enable Apache Spark(Pyspark) to run on Jupyter Notebook - Part 2 | Install Spark on Jupyter Notebook.
Run PySpark on Google Colab for FREE! | PySpark on Jupyter.
Simple Linear Regression using Spark MLLib | Introduction.
Simple Linear Regression using Spark MLLib | Data Preprocessing.
Simple Linear Regression using Spark MLLib | Build Train & Evaluate Model.
Simple Linear Regression | Scikit Learn & Spark MLLib | Model Evaluation Techniques - Part 1.
Simple Linear Regression | MSE RMSE & MAE | Model Evaluation Techniques - Part 2.
Multiple Linear Regression using Scikit Learn | Introduction & Intuition.
Multiple Linear Regression using Spark(PySpark) MLLib | Coding Part - 1.
Multiple Linear Regression using Spark(PySpark) MLLib | Coding Part - 2.
Multiple Linear Regression using Spark(PySpark) MLLib | Coding Part - 3.
Taught by
The AI University
