The potential for Machine Learning and Deep Learning practitioners to make a breakthrough and drive positive outcomes is unprecedented. But how do you take advantage of the myriad of data and ML tools now available at our fingertips? How to streamline processes, speed up discovery, and scale implementations for real-life scenarios?
Databricks provides you with ready-to-use clusters that can handle all analytics processes in one place, from data preparation to model building and serving, with virtually no limit so that you can scale resources as needed.
In this eBook, we will walk you through four Machine Learning use cases on Databricks:
- Loan Risk Use Case: We cover importing and exploring data in Databricks, executing ETL and the ML pipeline, including model tuning with XGBoost Logistic Regression.
- Advertising Analytics & Prediction Use Case: We walk through collecting and exploring the advertising logs with Spark SQL, using PySpark for feature engineering and using GBTClassifier for model training and predicting the clicks.
- Market Basket Analysis Problem at Scale: We show you everything from ETL to data exploration using Spark SQL, and model training using FT-growth.
- Suspicious Behavior Identification in Video Use Case: We review the pre-processing step to create image frames, transfer learning for featurization, and applying logistic regression to identify suspicious images in a video.