Yes, even you can create a machine learning (ML) model! Learn how in this hands-on demo with code and data we provide for you. You can watch the demo, or follow along with your own laptop, or download the code and data later and try it at home. During this session we will write Scala code using Spark and MLIB Decision Tree and Random Forest Classifiers to create your first ML model. If you don't know Scala or these frameworks, don't worry -- the examples are easy to follow, and you'll come away better prepared to do the same thing with the language and frameworks of your choice. Take away from the session: (a) code on GitHub having sample code in Scala implementing MLIB classifiers (b) code on GitHub that runs at scale within a Databricks If you want to follow along on your laptop, you should get set up before you arrive. (We do not have wi-fi access at our meeting location.) Download the code and data from this GitHub repository: https://github.com/aosama/MachineLearningSamples
In this webinar, we will cover some of the latest innovations brought into the Databricks Unified Analytics Platform for Machine Learning. In particular we will show you how to:
This free workshop, offered by Blue Granite and Microsoft, will provide attendees a deep dive experience into Azure Databricks, as well as hands-on lab experience with Spark.
Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure cloud services. With a broad set of capabilities that span data ingestion, storage, analytics, and streaming, it is becoming a popular choice for organizations with large data volumes. In this hand-on workshop, you will have the chance to create, configure, and interact with an instance of Azure Databricks - and learn how this new service can be a part of a modern data and analytics strategy.
Databricks speakers Jules S. Damji and Vendant Jain will be presenting at PyData Miami. Attend their talks and learn about MLflow, PySpark Structured Streaming and Apache Spark use case with IoT and Structured Streaming https://pydata.org/miami2019/
Let's meet up to kick off the great 2019 with some community discussion and the following line-up of topics: - The case for mlflow at GO-JEK, by Willem Pienaar, Data Science Platform Lead at GO-JEK - Project Hydrogen: State of the Art Deep Learning on Apache Spark, by Arseny Chernov, Lead of Partner Architecture APJ at Databricks. Venue Sponsor: WeWork Anson Road Food Sponsor: Databricks
In this webinar, we’ll show you how you can use MLlib with Azure Databricks to train your own models, run replicable experiments, and deploy into production with fewer failing jobs to accelerate your organization’s data science efforts.
The biggest barrier to successful machine learning projects is getting your data right. ShopRunner is synonymous with free shipping but fundamentally, is a data and technology company. Every month they collect many terabytes of data. They use that data to power truly differentiated shopping experiences at scale for millions of customers. ShopRunner has fielded numerous successful machine learning use cases personalization, recommendations, targeting and text, and image analysis.
The data team at Lennox International, a global leader in heating, air conditioning & refrigeration, was looking to establish a cost-effective data analytics platform in the cloud for processing inputs from millions of IoT devices.
Join Janath Manohararaj, Principal Big Data Architect at Lennox International, and Don Hilborn, Lead Solutions Architect at Databricks to learn how Databricks was deployed at Lennox to address data engineering challenges and improve cost-effectiveness.
In this webinar, we’ll teach you how to connect directly to TCP/IP ports and to streaming sources like Kafka, transform and output data, and finally create compelling continuously updated visualizations to drive greater impact for your teams.
Hi all, I'm happy to announce another Spark Meetup. This time Jelle Munk from Adyen will talk about their Data Api used by DS to analyse payment data. His collegue Serge Smertin will talk about automated data schema testing, and Niels Zeilemaker from GoDataDriven will talk about the lessons he learned while using DataBricks at Dynniq. The meetup will take place/is sponsored by Adyen. Agenda: 18:00: Arrive, mingle, food, drinks etc. 18:45: Data API - Jelle Munk The Adyen Data API provides an easy and consistent interface for all our data scientists and analysts to analyze payment data at scale. During this presentation, we dive into how we use Spark Dataframes to make these dynamic views and how we solved the problems we found along the way.