Databricks Linear Regression With Spark ML | Apache Spark MLlib
Apache Spark has a library for different types of machine learning models. In this tutorial, we will talk about how to use Databricks to implement the spark ML linear regression model. We will cover:
👉 What's the difference between Spark MLlib and Spark ML?
👉 How to process the data in the right format?
👉 How to fit a Spark ML linear regression model?
👉 How to evaluate model performance?
👉 How to save the model?
👉 How to make predictions for new data?
⏰ Timecodes ⏰
0:00 - Intro
0:28 - Step 0: Spark MLlib Vs. Spark ML
0:59 - Step 1: Import Libraries
1:24 - Step 2: Create Dataset For Linear Regression
2:01 - Step 3: Train Test Split
2:31 - Step 4: Vector Assembler
2:46 - Step 5: Fit Spark ML Linear Regression Model
3:27 - Step 6: Model Performance Evaluation
4:24 - Step 7: Save Model
4:48 - Step 8: Make Predictions For New Data
5:11 - Summary
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