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Data Skeptic

Latest episodes

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Aug 12, 2022 • 30min

ML Ops Best Practices

Today, we are joined by Piotr Niedźwiedź, Founder and CEO of Neptune.ai. Piotr discusses common MLOps activities by data science teams and how they can take advantage of Neptune.ai for better experiment tracking and efficiency. Listen for more!
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Aug 8, 2022 • 52min

Affiliate Marketing Rabbithole

Affiliate marketing creates an opportunity for marketers to gain a commission by promoting a product or service.  Cookies are typically used for tracking and the advertiser whose product or service is being featured pays the marketing only on transactions. Today's episode covers those approaches and is also a story of conflict between two large companies and how one affiliate marketer got caught in the middle.
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Aug 1, 2022 • 54min

Monetization of Youtube Conspiracy Theorists

Cameron Ballard joins us today to discuss his work around YouTube conspiracy theories. He revealed interesting observations about conspiracy theories on YouTube including how predatory ads are most common in conspiracy theory videos and how YouTube’s algorithm subtly works for predatory ads. 
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Jul 25, 2022 • 38min

User Perceptions of Problematic Ads

Eric Zeng joins us to discuss his study around understanding bad ads and efforts that can be taken to limit bad ads online. He discussed how he and his co authors scrapped a large amount of ad data, applied a machine learning algorithm, and commensurate statistical results.
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5 snips
Jul 21, 2022 • 36min

Political Digital Advertising Analysis

NaLette Brodnax, a political scientist and an Assistant Professor in the McCourt School of Public Policy at Georgetown University joins us to discuss her work on analyzing digital advertisements for political campaigns. She used data for electoral campaigns on Facebook to answer questions that help us better understand how digital ads affect the outcome of elections.   Click here for additional show notes! Thanks to our sponsor! https://neptune.ai/ Log, store, query, display, organize and compare all your model metadata in a single place
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Jul 18, 2022 • 36min

Fraud Detection in Crowdfunding Campaigns

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Jul 11, 2022 • 43min

Artificial Intelligence and Auction Design

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Jul 4, 2022 • 33min

Privacy Preference Signals

Have you ever wondered what goes on under the hood when you accept a website’s cookies? Today, Maximilian Hils, a PhD student in Computer Science, at the University of Innsbruck, Austria, dissects the ad tech industry and the standards put in place to protect users’ data. He also shares his thoughts on the use of VPNs as well as other tools that help shield your data from prying eyes on the internet. Click here for additional show notes Thanks to our sponsor: https://clear.ml/ ClearML is an open-source MLOps solution users love to customize, helping you easily Track, Orchestrate, and Automate ML workflows at scale.
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Jun 27, 2022 • 28min

Neural Architecture Search for CTR Prediction

Ravi Krishna joins us today to talk about his recent work on a differentiable NAS framework for ads CTR prediction. He discussed what CTR prediction is about and why his NAS framework helps in building neural networks for better ads recommendation. Listen to learn about methodology, related literature and his results. Click for additional show notes Thanks to our sponsor: https://astrato.io Astrato is a modern BI and analytics platform built for the Snowflake Data Cloud. A next-generation live query data visualization and analytics solution, empowering everyone to make live data decisions.
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9 snips
Jun 21, 2022 • 44min

Algorithmic PPC Management

Effectively managing a large budget of pay per click advertising demands software solutions. When spending multi-million dollar budgets on hundreds of thousands of keywords, an effective algorithmic strategy is required to optimize marketing objectives. In this episode, Nathan Janos joins us to share insights from his work in the ad tech industry. Click for additional show notes Thanks to our sponsor! https://wandb.com/ The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management.

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