Machine Learning In The Enterprise - Dev-Lifecycle, ML-Apps & ML-Opps

In this talk today, we will walk through what the current landscape of ML Operations in the Enterprise looks like, consider some of the main challenges faced and discuss a few different approaches to overcoming these challenges. Adjusting and adopting ML models to accommodate new sets of data or more heavily consider one factor as opposed to another is often an especially challenging concept when dealing with such large sets of data and so many different parameters. Managing and optimally manipulating this landscape is where Cloudera is now heavily involved to try and make this process more transparent and easier. There will thus be a deeper dive into this specific aspect as well.