The Disney Data & Analytics Conference 2018 will bring together over 1,300 executives, managers, and analysts representing over 200 companies and universities, plus all segments of The Walt Disney Company, including Parks & Resorts, Media Networks, Studio Entertainment, and Consumer Products & Interactive Media. Attendees represent an array of analytic disciplines including Revenue Management, Pricing, Forecasting, Marketing Analytics, CRM, Research, Technology, Data Management, and Decision Science.
Andre Mesarovic will be speaking about an exciting new open source project ML Flow https://mlflow.org/
In our webinar, we will present MLflow, a new open source project from Databricks that aims to design an open ML platform where organizations can use any ML library and development tool of their choice to reliably build and share ML applications. MLflow introduces simple abstractions to package reproducible projects, track results, and encapsulate models that can be used with many existing tools, accelerating the ML lifecycle for organizations of any size.
Please join us for the next Spark London Meetup! We have two talks discussing building Apache Spark apps and Pyspark and the Apache Arrow integration. As usual, there will be beer and pizza available courtesy of our sponsors Capgemini and Databricks - so please do come along! Networking and drinks will be from 6:30pm with the talks starting around 7pm.
In this workshop we’ll uncover the challenges of big data and ML, best practices for enterprises to use Apache Spark and the cloud to simplify and scale your data analytics efforts. We’ll dive into the components of Apache Spark, how Spark is used for common use cases such as ETL, SQL analytics, and machine learning, and how taking the power of Apache Spark to the cloud with the Databricks Unified Analytics Platform can simplify data engineering operations and accelerate data science innovation.
The Artificial Intelligence Conference brings the growing AI community together to explore the most essential issues and intriguing innovations in applied AI. We'll delve into practical business applications, compelling use cases, rock-solid technical skills, tear-downs of successful AI projects, and dissections of failures in these key topic areas: AI in the enterprise: Executive Briefings, case studies and use cases, industry-specific applications -The impact of AI on business and society: automation, safety, regulation -Implementing AI projects: applications, tools, architecture, security -Interacting with AI: design, metrics, product management, bots -Models and methods: algorithms, vision/speech/emotion, deep learning, data, training
After a long hiatus, the SF PyData meetup group is BACK! Starting Sept 6th, we're going to return to having regular, in-person meet ups in San Francisco. The usage of Python and PyData tools has grown explosively over the last few years, and we're very excited to start building a community where data lovers from all across the Bay Area can meet, connect, and learn from each other. To kick off the new series we've got a great line up of speakers who'll teach us about 1) managing the complete machine learning lifecycle and 2) producing clear, effective visualizations of scientific data.
Plumbing has been a key focus of modern software engineering, with our API/services/containers/devops driven landscape so it may come as a surprise that plumbing is where AI projects tend to fail. But it is precisely because our modern software development focuses on decoupled plumbing that we have struggled to handle the rise of AI. Specifically, companies are able to use AI effectively when they are able to create end-to-end AI model factories that explicitly account for coupling between data, models, and code. In this talk, I will be walking through what a model factory is and how MLFlow's design supports the creation of end-to-end model factories as well as sharing best practices I've observed helping customers from startups to Fortune 50s create, productionize, and scale end-to-end ML pipelines, and watching those pipelines produce serious, game-changing business impact.
Every enterprise today wants to accelerate innovation by building AI into their business. However, most companies struggle with managing and preparing large datasets for analytics; complexity of managing an explosion of ML frameworks and moving models in development to production. Join this ½ day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts.
Every year thousands of top data scientists, analysts, engineers, and executives converge at Strata Data Conference—the largest gathering of its kind. It's where technologists and decision makers turn data and algorithms into business advantage. Data and AI technology drive everything—from competitive strategy and new lines of business, to supply and logistics, to customer management and marketing automation. At Strata, you'll learn what you need to succeed: -Achieve demonstrable ROI for your data projects -Increase efficiency and innovation -Reduce costs and risk -Build security, compliance, and transparency into your data products -Apply new machine learning techniques to solve business problems -Architect data applications that achieve your specific goals—whether it's fraud detection, targeting & segmentation, or anticipating your customer's next moves