Highlights from the Strata Data Conference in San Jose 2018

Watch highlights covering machine learning, business intelligence, data privacy, and more. From the Strata Data Conference in San Jose 2018.

By Mac Slocum
March 7, 2018
Strata Data Conference 2018 in San Jose Strata Data Conference 2018 in San Jose (source: O'Reilly Conferences via Flickr)

Experts from across the data world came together in San Jose, California for the Strata Data Conference. Below you’ll find links to highlights from the event.

Merging human and machine learning for everyday solutions

Li Fan shows how Pinterest is using AI to predict what’s in an image, what a user wants, and what they’ll want next.

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To a hammer, everything is a nail: Choosing the right tool for your business problems

Tobias Ternstrom explains why you should objectively evaluate the problem you’re trying to solve before choosing the tool to fix it.

Privacy in the age of machine learning

Ben Lorica explores emerging security best practices for business intelligence, machine learning, and mobile computing products.

Crisis Text Line data usage and insights

Nancy Lublin and Bob Filbin explore findings from crisis data.

Defining responsible data practices: A community-driven approach

Natalie Evans Harris discusses the Community Principles on Ethical Data Practices (CPEDP), a code of ethics for data collection, sharing, and utilization.

Operationalizing machine learning

Dinesh Nirmal explains how real-world machine learning reveals assumptions embedded in business processes that cause expensive misunderstandings.

Data science in the cloud

Alex Smola shares lessons learned from AWS SageMaker, an integrated framework for handling all stages of analysis.

Sprouted clams and stanky bean: When machine learning makes mistakes

Using silly datasets as examples, Janelle Shane talks about ways that algorithms fail.

The case for a deliberate data strategy in today’s attention-deficit economy

Anoop Dawar shares principles successful companies are using to inspire an insight-driven ethos and build data-competent organizations.

Differentiating via data science

Eric Colson explains why companies must now think very differently about the role and placement of data science in organizations.

What separates the clouds?

William Vambenepe walks through an interesting use case of machine learning in action and discusses the central role AI will play in big data analysis moving forward.

Inclusivity for the greater good

Ajey Gore explains why GO-JEK is focusing its attention beyond urban Indonesia to help people across the country’s rural areas.

Lessons in Google search data

Seth Stephens-Davidowitz explains how to use Google searches to uncover behaviors or attitudes that may be hidden from traditional surveys.

Post topics: AI & ML, Data

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