Udemy has over two million students who are learning Machine Learning on the platform. Many of these students are aspiring entrepreneurs.
Here is a list of Udemy entrepreneurship courses based on the 1Mby1M methodology that would help them put one foot before the other to get a startup strategy figured out.>>>
Sridhar Iyengar: In 2011, my business partner and I started our second venture together. It was a wearable tech company called Misfit Wearables. We were heavily inspired by the digital health area that we were exposed to. We wanted to do something in digital health.
Back in 2010, the only way to do that was to not be a medical device, but to be a consumer electronics product. We made fitness trackers. We grew that rapidly and sold that to Fossil. What was interesting about that was that our fitness trackers were just motion sensors. We had almost a million people using them all over the world.>>>
Sramana Mitra: We’ve talked about the use case and data signals. When you started, how did you get the data with which to train the model, and what was the seeding of the algorithm?
Sivakumar Lakshmanan: We are single-tenant. We don’t train our models on one customer and use them for other customers because of the sensitivities involved in retail sales data and consumer product sales data. We train the model on our customer’s information. The seeding happens for individual customers and not on the industry.>>>
Sramana Mitra: Is this the use case that you started your company with?
Sivakumar Lakshmanan: There are two primary use cases. One is around forecasting and the other is a pricing use case. The pricing use case determines the price at the retail shelf and how to mark down the product.
Sramana Mitra: Why don’t we do the pricing use case?>>>
Siva has bootstrapped an AI SaaS company with Services. He shares invaluable insights on accessing data for building AI models and product strategy choices the company has made.
Sramana Mitra: Let’s start by having you introduce yourself to our audience as well as to Antuit.>>>
Sramana Mitra: Do you see Cassandra a lot?
Josh Odmark: Yes, it’s been popping up a lot more lately when it comes to machine learning because of its read and write speed. People treat it both as a traditional datastore and also an intermediary. With data science, there’s typically layers to your model or a bunch of steps you need to take until you get to your model. We see Cassandra being used both as a data store and a place to put the intermediary steps. In the streaming space, Cassandra is popular.>>>
Gideon Rubin: Then once they had that estimate and were comfortable moving ahead, then we pull in the data and every day, we process. It changes the bids across Google and other channels. It updates the budgets. It keeps reprocessing. We allow them to access the data. We allow them to automate the movement of the data. At the end, we allow them to get insights that enable their clients to be highly successful in their marketing campaign.
With that new positioning, they went public in August pushing machine learning as a core competency. For that 140-team that I mentioned, the product is 500% larger as far as customer base now than what it was when we started. They cut down from six data scientists to four. Their DevOps were cut drastically. That’s just one example.>>>
We explore AI Connectivity in this discussion.
Sramana Mitra: Let’s start by having the two of you introduce yourselves as well as Pandio.
Gideon Rubin: I’m the CEO and Co-Founder along with Josh Odmark. I’m a serial entrepreneur. I focus primarily on using big data and data science to gain an advantage. Pandio came from the fact that Josh and I both came from different startups. We were talking about what to do next. We realized that IoT and a lot of the data sources were getting really good.>>>