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The key to value creation in the Internet of Things is the model. The model is used by both the app and analytics. It quantifies the value proposition, so the better the model, the higher the value. Developing these models in traditional markets is time consuming enough but given the volume, velocity and variety of IoT data, the load on the IoT data scientist can be overwhelming. Enter machine learning or ML for short. Machine learning can augment the skills of the data scientist by helping to select the algorithms or weighted ensemble of algorithms that provide the underlying structure for the model.
Watch this video (or read the transcript) video to see Rob Patterson discuss how machine learning is being used to help create and maintain Internet of Things models ...




Episode 26

OK, get ready for it, we’re going to get down and dirty with predictive analytics and when I say dirty, I mean the mathematics of the different forms of predictive models dirty. Geek fest? Yes, but close your eyes and extrapolate how predictive analytics can be applied to your situation. By understanding how it works you will also understand the limits of what it can and cannot do.
Listen to this podcast (or read the transcript) with Anil Gandhi and emerge with a better understanding of predictive analytics and how it really relates to real-time and descriptive analytics ...




Episode 25

First it was Big Data and now it’s the Internet of Things; the science of data is becoming increasingly sexy, maybe not Victoria’s Secret sexy but it certainly get the juices flowing for business leaders in the know. Hot or not? Definitely hot.
Listen to this podcast (or read the transcript) with Ajit Jaokar about his passion, data science, and the application of machine learning, deep learning and predictive analytics in IoT ...