HusainAl-Mohssen
Husain's main focus is in the area of engineering science and it's application to create profitable products that serve 10's or 100's of thousands of users. Husain's work at MIT focused on extracting faint signals from super-computer scale gas simulations close to equilibrium. He later built on this background to start a user-facing email analytics company that serviced thousands of paying customers in near-real time. Husain has extensive software engineering experience both as a developer, maintainer and architect in the areas of enterprise software, high performance computing, as well as the “Big Data” domain. Husain is also an accomplished mechanical engineer, with many years of hands-on experience in the oil and power industries.
Sooner or later you probably will be working on a projects with words like “Data Science”, “Machine Learning”, “Big Data" attached to them. This talk will help you deliver these projects successfully by reviewing the key items you need to consider when incorporating analytical solutions into shipping products.
Humanity has dramatically increased it’s ability to generate and retain astronomically large amounts of data in the last decade. Sooner or later you probably will be working on a project that will have a significant “Data Science” component to it or at least be expected to give input about building such system. This is the second of a two-part introduction using machine learning techniques to solve data science questions using the R programming language.
Zero fluff.