The Right (big data) Tool for the Job with Jay Shankar
Data Skeptic7 Heinä 2014

The Right (big data) Tool for the Job with Jay Shankar

In this week's episode, we discuss applied solutions to big data problem with big data engineer Jay Shankar. The episode explores approaches and design philosophy to solving real world big data business problems, and the exploration of the wide array of tools available.

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Tribal Marketing

Tribal Marketing

Peter Gloor, a Research Scientist at the MIT Center for Collective Intelligence, takes us on a new world of tribe classification. He extensively discussed the need for such classification on the internet and how he built a machine learning model that does it. Listen to find out more!

24 Loka 202237min

Nano-targetted Facebook Ads

Nano-targetted Facebook Ads

17 Loka 202244min

Debiasing GPT-3 Job Ads

Debiasing GPT-3 Job Ads

We hear about the impeccable achievements of GPT-3 models, but such large generative models come with their bias. On the show today, Conrad Borchers, a Ph.D. student in Human-Computer Interaction, joins us to discuss the bias in GPT-3 for job ads and how such large models can be de-biased. Listen to learn more!

10 Loka 202248min

ML Ops in Production

ML Ops in Production

Moses Guttman from Clear ML joins us to share insights about how organizations leveraging machine learning keep their programs on track. While many parallels exist between the software development life cycle (SWLC) and the machine learning development life cycle, successful deployments of ML in production have demonstrated that a unique set of tools is required. Moses and I discuss the emergence of ML Ops, success stories, and how modern teams leverage tools like Clear ML's open source solution to maximize the value of ML in the organization.

6 Loka 202241min

Ad Network Tomography

Ad Network Tomography

Data sharing in the ad tech space has largely been a black box system. While it is obvious the data is being collected, the data sharing process is obscure to users. On the show today, Maaz Bin Musa and Rishab, both researchers at the University of Iowa, speak about the importance of data transparency and their tool, ATOM for data transparency. Listen to find out how ATOM uncovers data-sharing relationships in the ad-tech space.

3 Loka 202235min

First Party Tracking Cookies

First Party Tracking Cookies

When you accept cookies on a website, you cannot tell whether the cookies are used for tracking your personal data or not. Shaoor Munir's machine learning model does that. On the show today, the Ph.D student at the University of California, discussed the world of first-party cookies and how he developed a machine learning model that predicts whether a first-party cookie is used for tracking purposes.

26 Syys 202235min

The Harms of Targeted Weight Loss Ads

The Harms of Targeted Weight Loss Ads

Liza Gak, a Ph.D. student at UC Berkeley, joins us to discuss her research on harmful weight loss advertising. She discussed how weight loss ads are not fact-checked, and how they typically target the most vulnerable. She extensively discussed her interview process, data analysis, and results. Listen for more!

19 Syys 202234min

Podcast Advertising

Podcast Advertising

Growing your podcast to the point of monetization is not a walk in the park. Today, Rob Walch, the VP of Podcast Relations at Libsyn talks about podcast advertising. He discussed how advertising works, how to grow your audience and some blueprints to being a successful podcaster. Listen for more.

12 Syys 202235min

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