Blog

Data Tools Deep Dive: Machine Learning

Contributing Author: Dr. Michael Tamir Whether you knew it or not, you’ve probably been taking advantage of the benefits of machine learning for years. Most would find it hard to go a full day without using at least one app or web service driven by machine learning. Amazon, Facebook, Netflix, and, of course, Google all have been using machine learning algorithms to drive searches, recommendations, targeted advertising, and more for well over a decade. In recent years, letting algorithms sort through a company’s data to find out how to optimize a business has become the rule rather than the exception. […]

Industrial Internet: Big Data and Analytics Driving Big Outcomes

The torrent of data generated from machines, networks, devices, and data centers in industry verticals provide challenges and opportunities. The challenge is to make this machine data meaningful and actionable to deliver on opportunities around operational efficiencies. On March 15, Beena Ammanath, Vice President of Data Science at General Electric, joined datascience@berkeley to present “Industrial Internet: Big Data and Analytics Driving Big Outcomes.” Ammanath shared real-world case studies demonstrating tangible operational benefits by tightly integrating machines, networked sensors, industrial-strength data, and software to enable intelligent insights and affect measurable outcomes. Here, we provide a recap of her presentation and key takeaways about how the Industrial Internet is making the most of big data to drive big outcomes. 

 

Synthetic Capstone Spotlight: AidSight

The Master of Information and Data Science (MIDS) program at the UC Berkeley School of Information (I School) culminates with a synthetic capstone project. One capstone team consisting of MIDS students Nicholas Hamlin External link Natarajan Krishnaswami External link Glenn Dunmire External link , and Minhchau Dang External link  came together to create AidSight External link . AidSight is a platform that uses modern data science techniques to make the 600,000 aid activities reported to the International Aid Transparency Initiative External link  (IATI) understandable and digestible at a glance. The AidSight team took some time to answer a few questions we had about the impact their platform is having on the global aid and funding community.

Michael Nielsen: Open Science Now!

In this 2011 TED Talk, quantum physicist turned writer Michael Nielsen explains the need for a second revolution of open science that translates to the data science world. Due to today’s available technologies, Nielsen sees incredible potential for immediate global collaboration that could advance science at a rate never thought possible.

 

MIDS Fall 2016 Capstone Presentations

On December 19th, the fall 2016 datascience@berkeley graduates presented their capstone projects in a public webinar. For the capstone project, the graduates were tasked to solve a real-world situation or problem utilizing their data science skills in communication, problem-solving, influence, and management to provide a fully realized solution.

Performant Deep Learning at Scale with Apache Spark & Apache SystemML

Machine learning continues to deepen its impact with new platforms that enable more efficient and accurate analysis of big data. One such platform is Apache SystemML External link , which allows for large-scale learning on the underlying Apache Spark External link  platform, while maintaining the simple, modular, high-level mathematics at the core of the field. In a recent webinar, Mike Dusenberry External link , an engineer at the IBM Spark Technology Center External link  presented the work he and his team are doing to create a deep learning library for SystemML and solve for performant deep learning at scale. Here, we’ll provide the key points that Mike discussed, as well as additional resources for further exploration.

MIDS Summer 2016 Capstone Presentations

On August 25, the summer 2016 datascience@berkeley graduates presented their capstone projects in a public webinar. For the capstone project, the graduates were tasked to solve a real-world situation or problem utilizing their data science skills in communication, problem-solving, influence, and management to provide a fully realized solution

MIDS Program: 2016 Status Report

When we launched the Master of Information and Data Science (MIDS) program in January of 2014, we knew that we were taking a calculated risk. The data science field was gaining momentum, but there weren’t many established professional data science master’s degree programs in existence. This presented the I School with the opportunity to be one of the first movers in the space and, consequently, carve out a unique role in shaping the future of data science education.

MIDS Spring 2016 Capstone Presentations

On May 2, the spring 2016 datascience@berkeley graduates presented their capstone projects in a public webinar. For the capstone project, the graduates were tasked to solve a real-world situation or problem utilizing their data science skills in communication, problem-solving, influence, and management to provide a fully realized solution.

Applications in Data Science Webinar Series Recap: Data Science For Social Good

In a recent webinar hosted by datascience@berkeley, JeanCarlo “JC” Bonilla, Director of Insight and Impact at DataKind, shared his perspective on how data science can be used to not only make better decisions about the movies we watch — but also how to make our world a better place. Participants from around the world tuned in to his one-hour presentation to listen as he explored the use of data for social good.