1 -About this section
2 -Learning about Machine Learning
3 -How to build a Machine Learning Model
4 -Apache Spark MLLib Overview
5 -Learning about ML Pipelines using Spark MLlib
6 -Data Sources by Spark MLlib to Build ML Models
7 -Create DataFrames from Data Sources
7 -Section10 - 00 - Resources.zip
8 -Learning about Featurization using Spark MLlib
9 -Using Apache Spark MLlibs - Feature Transformers
10 -Using Tokenizer
11 -Using StringIndexer
12 -Using Pipelines
13 -Using VectorAssembler
14 -Using VectorIndexer
15 -Using MLlib Estimator - Linear Regression
16 -Using MLlib Estimator - Logisitic Regression
17 -Measure ML Effiecny using Spark MLlib Evaluators
18 -Using ML for Solving Real World Problem
19 -Building ML Model P1 - Using Local Host
20 -Building ML Model P2 - Using Databricks Community Edition
21 -Using Apache Spark MLFlow with Databricks Community Edition
