Neil Batlivala public
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Pedro compares the state of ML now to the beginning of the aviation industry; early pilots needed to know everything from the physics of flight to the engineering behind the plan and nowadays, a pilot interfaces with the entire plane through a cockpit dashboard. Ople AI is trying to be that dashboard, hiding implementation details of training to al…
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NanoNets is a Machine Learning as a Service platform for developers to rapidly create/deploy models. Learn about how they do it with transfer learning, a technique that uses learnings from coarse models to bolster others. They have a product aimed at developers and give insights into where ML tech is going!…
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Sales is a game of managing customer leads, pipelines, and followups. People.AI is automating the sales manager to help you close more deals backed by some unexpected yet highly reliable data sources. This interview we focus on the advantages of using high quality data sets and starting off as a consulting shop, to help build out new models that yo…
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Learn how Adam and the team at LiftIgniter are bringing innovations from Google to the rest of the business world. Google, whose main revenue come from ads, has developed arguably the world’s most sophisticated machine learning for ad targeting. Lift Igniter is taking similar concepts and creating a bleeding edge personalization engine that ups use…
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Preteckt is an ingenious cross between a IoT and ML company. The company uses its own hardware sensors to determine when a customer's 16 wheeler is going to break down. In this episode, we talk about how to optimize for data growth and not revenue growth when first starting a ML company. Its the ultimate positive feedback loop of Customer -> More D…
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Kylie.ai is a service that automates customer service tickets. This is a longer than average episode as Sinan’s interview was too good to be cut down any shorter. We dive in on building models per rep, and how Sinan was able to train a model using public Twitter data so that he could have a customer solution before even stepping into a meeting! A f…
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