Simplify Market Basket Analysis using FP-growth on Databricks
When providing recommendations to shoppers on what to purchase, you are often looking for items that are frequently purchased together (e.g. peanut butter and jelly). A key technique to uncover associations between different items is known as market basket analysis. In your recommendation engine toolbox, the association rules generated by market basket analysis (e.g. if...
Identify Suspicious Behavior in Video with Databricks Runtime for Machine Learning
With the exponential growth of cameras and visual recordings, it is becoming increasingly important to operationalize and automate the process of video identification and categorization. Applications ranging from identifying the correct cat video to visually categorizing objects are becoming more prevalent. With millions of users around the world generating and consuming billions of minutes of...
MLflow On-Demand Webinar and FAQ Now Available!
On August 30th, our team hosted a live webinar—Introducing MLflow: Infrastructure for a complete Machine Learning lifecycle—with Matei Zaharia, Co-Founder and Chief Technologist at Databricks. In this webinar, we walked you through MLflow, a new open source project from Databricks that aims to design an open ML platform where organizations can use any ML library...
Introducing Cluster-scoped Init Scripts
This summer, I worked at Databricks as a software engineering intern on the Clusters team. As part of my internship project, I designed and implemented Cluster-scoped init scripts, improving scalability and ease of use. In this blog, I will discuss various benefits of Cluster-scoped init scripts, followed by my internship experience at Databricks, and the...
Announcing Databricks Runtime 4.3
I'm pleased to announce the release of Databricks Runtime 4.3, powered by Apache Spark. We've packed this release with an assortment of new features, performance improvements, and quality improvements to the platform. We recommend moving to Databricks Runtime 4.3 in order to take advantage of these improvements. In our obsession to continually improve our platform’s...
Building a Real-Time Attribution Pipeline with Databricks Delta
In digital advertising, one of the most important things to be able to deliver to clients is information about how their advertising spend drove results. The more quickly we can provide this, the better. To tie conversions or engagements to the impressions served in an advertising campaign, companies must perform attribution. Attribution can be a...
Loan Risk Analysis with XGBoost and Databricks Runtime for Machine Learning
For companies that make money off of interest on loans held by their customer, it’s always about increasing the bottom line. Being able to assess the risk of loan applications can save a lender the cost of holding too many risky assets. It is the data scientist’s job to run analysis on your customer data...
Simplify Advertising Analytics Click Prediction with Databricks Unified Analytics Platform
Advertising teams want to analyze their immense stores and varieties of data requiring a scalable, extensible, and elastic platform. Advanced analytics, including but not limited to classification, clustering, recognition, prediction, and recommendations allow these organizations to gain deeper insights from their data and drive business outcomes. As data of various types grow in volume, Apache...
Simplify Streaming Stock Data Analysis Using Databricks Delta
Traditionally, real-time analysis of stock data was a complicated endeavor due to the complexities of maintaining a streaming system and ensuring transactional consistency of legacy and streaming data concurrently. Databricks Delta helps solve many of the pain points of building a streaming system to analyze stock data in real-time. In the following diagram, we provide...
Make Your Oil and Gas Assets Smarter by Implementing Predictive Maintenance with Databricks
How to build an end-to-end predictive data pipeline with Databricks Delta and Spark Streaming Maintaining assets such as compressors is an extremely complex endeavor: they are used in everything from small drilling rigs to deep-water platforms, the assets are located across the globe, and they generate terabytes of data daily. A failure for just one...
