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Data Science 101: Machine Learning – The Basics

The next installment of insideBIGDATA’s Data Science 101 series comes from our friends over at LinkedIn.

Data Science 101: Random Forests

Machine_Learning

The Random forests machine learning algorithm is a popular ensemble method used by many data scientists to achieve good predictive performance in the classification regime. Fully understanding the nuances of this statistical learning technique is paramount to getting the most out of this algorithm – unfortunately, this means math. The presentation below is from machine learning course CPSC 540 at The University of British Columbia,

Dr. Max Kuhn Interviewed at useR! Conference

Data Science

In the presentation below, data scientist, author (“Applied Predictive Modeling” with Kjell Johnson) and R caret package developer Max Kuhn sits down for an in-depth interview with Eduardo Arino de la Rubia sponsored by our friends over at DataScience.LA. They discuss the art and science of predictive modeling in the real world, the multifaceted and […]

Data Science 101: Using Statistics to Predict AB Testing

Slide1

The talk below presents simple methods that can accurately predict future performance from AB test results, and that allow you to determine the smallest acceptable sample size. Using four years of AB testing data, you’ll see how these methods really work.

Data Science 101: Lessons Learned from Kaggle Competitions

kaggle_monster

In the video presentation below, “Machine learning best practices we’ve learned from hundreds of competitions,” Ben Hamner, Chief Scientist at Kaggle, discusses some very intriguing insights into how find success in data science projects.

Confessions of a Recovering Data Broker

ToServeMan

Do data brokers act to serve man? Decide for yourself. The full title of the talk below is “Confessions of a Recovering Data Broker: Responsible Innovation in the Age of Big Data, Big Brother, and the Coming Skynet Terminators.” The presenter is Jim Adler, VP of Products, Metanautix.

The Rise of Data Science in the Age of Big Data Analytics

Data Science is the key to unlocking insight from Big Data: by combining computer science skills with statistical analysis and a deep understanding of the data and problem we can not only make better predictions, but also fill in gaps in our knowledge, and even find answers to questions we hadn’t even thought of yet.

The Future of AI – A Fireside Chat by Yann Lecun, Facebook

In the thought-provoking video below, Professor Yann LeCun, Director of AI Research at Facebook, sat down for a fireside chat at December 2014’s edition of Data Driven NYC to discuss deep learning and the future of artificial intelligence.

Data Just Right: A Practical Introduction to Data Science Skills

datascientist

The presentation below is from the DataEDGE 2013 conference sponsored by the UC Berkeley School of Information – “Data Just Right: A Practical Introduction to Data Science Skills,” featuring Michael Manoochehri, Developer Programs Engineer, Google.

Why Data Science Will Power the Future

Data Science

The presentation below, “Why Data Science Will Power the Future,” is brought to you by our friends over at Udacity. Featured are members of the Udacity team including CEO Sebastian Thrun, and Vice President of Engineering and Data Science Nitin Sharma.