Efficient Databricks Deployment Automation with Terraform

Posted Leave a commentPosted in CI/CD, cloud automation, Company Blog, Customers, Ecosystem, Education, Engineering Blog, Platform

Managing cloud infrastructure and provisioning resources can be a headache that DevOps engineers are all too familiar with. Even the most capable cloud admins can get bogged down with managing a bewildering number of interconnected cloud resources – including data streams, storage, compute power, and analytics tools. Take, for example, the following scenario: a customer […]

Detecting Financial Fraud at Scale with Decision Trees and MLflow on  Databricks

Posted Leave a commentPosted in Apache Spark, Company Blog, Decision tree, Education, Engineering Blog, financial, Financial Markets, Financial Services, Fraud, Fraud Detection, Machine Leanring, Machine Learning, Platform

Try this notebook in Databricks Detecting fraudulent patterns at scale is a challenge, no matter the use case. The massive amounts of data to sift through, the complexity of the constantly evolving techniques, and the very small number of actual examples of fraudulent behavior are comparable to finding a needle in a haystack while not […]

Understanding Dynamic Time Warping – The Databricks Blog

Posted Leave a commentPosted in Apache Spark, Company Blog, Dynamic Time Warping, Education, Engineering Blog, Machine Learning, Platform

Try this notebook in Databricks This blog is part 1 of our two-part series Using Dynamic Time Warping and MLflow to Detect Sales Trends. To go to part 2, go to Using Dynamic Time Warping and MLflow to Detect Sales Trends. The phrase “dynamic time warping,” at first read, might evoke images of Marty McFly […]

Using Dynamic Time Warping and MLflow to Detect Sales Trends

Posted Leave a commentPosted in Apache Spark, Company Blog, Dynamic Time Warping, Education, Engineering Blog, Machine Learning, MLflow, Platform

Try this notebook series in Databricks This blog is part 2 of our two-part series Using Dynamic Time Warping and MLflow to Detect Sales Trends.  The phrase “dynamic time warping,” at first read, might evoke images of Marty McFly driving his DeLorean at 88 MPH in the Back to the Future series. Alas, dynamic time warping does […]

Introducing MLflow Run Sidebar in Databricks Notebooks

Posted Leave a commentPosted in Announcements, Company Blog, Engineering Blog, Machine Learning, Managed MLflow, MLflow, Platform, Sidebar

At Spark+AI Summit 2019, we announced the GA of Managed MLflow on Databricks in which we take the latest and greatest of open source MLflow and make it easily accessible to all users of Databricks. In that blog post, we promised to build features which bridge Databricks and MLflow concepts to create a seamless integration […]

Announcing General Availability of Managed MLflow on Databricks

Posted Leave a commentPosted in Announcements, Company Blog, Ecosystem, Engineering Blog, Machine Learning, Managed MLflow, MLflow, Platform, Product

Try this tutorial in Databricks MLflow is an open source platform to help manage the complete machine learning lifecycle. With MLflow, data scientists can track and share experiments locally or in the cloud, package and share models across frameworks, and deploy models virtually anywhere. Today at the Spark + AI Summit, we announced the General […]

Koalas: Easy Transition from pandas to Apache Spark

Posted Leave a commentPosted in Announcements, Apache Spark, Company Blog, Data Science, Ecosystem, Education, Engineering Blog, Machine Learning, Open Source, Pandas, python

Today at Spark + AI Summit, we announced Koalas, a new open source project that augments PySpark’s DataFrame API to make it compatible with pandas. Python data science has exploded over the past few years and pandas has emerged as the lynchpin of the ecosystem. When data scientists get their hands on a data set, […]

Databricks Runtime 5.3 ML Now Generally Available

Posted Leave a commentPosted in Announcements, Company Blog, Data Science, Databricks Runtime 5.3 ML, Deep Learning, Ecosystem, Engineering Blog, Machine Learning, Product

We are excited to announce the general availability (GA) of Databricks Runtime for Machine Learning, as part of the release of Databricks Runtime 5.3 ML. Built on top of Databricks Runtime, Databricks Runtime ML is the optimized runtime for developing ML/DL applications in Databricks. It offers native integration with popular ML/DL frameworks, such as scikit-learn, […]

Introducing Brickchain: Planet-scale Unified Analytics

Posted Leave a commentPosted in Apache Spark, Ecosystem, Engineering Blog, Machine Learning, Unified Analytics Engine

Today we are excited to announce Brickchain, the next generation technology for zettabyte-scale analytics, by harnessing all the compute power on the planet. Brickchain is the most scalable, secure, and collaborative data technology ever invented. As you may know, Databricks was founded by the original creators of Apache Spark, a unified analytics engine that uses […]