Brought to you by our friends over at the Stanford Center for Professional Development is this compelling data science education resource: “Expressing yourself in R” – by Hadley Wickham, Rice University.
Provided by our friends over at Edureka, Module 1 of their Apache Cassandra course below discusses the fundamental concepts of using a highly-scalable, column-oriented database to implement appropriate use cases.
Support Vector Machines (SVM) is an important and widely used machine learning algorithm. In order to fully understand SVMs, you need to have a fundamental understanding of how the statistical learning method functions. Here is a useful lecture on SVM coming from MIT OpenCourseware.
The video presentation below is a highly compelling talk by Stanford University professor and Coursera co-founder, Dr. Andrew Ng. Andrew addresses a graduate summer school audience at UCLA’s IPAM (Institute for Pure & Applied Mathematics) on the topic – Deep Learning, Feature Learning.
Mining Big Data can be an incredibly frustrating experience due to its inherent complexity and a lack of tools.
From the SciPy2013 conference, here is a compelling talk “Data Agnosticism: Feature Engineering Without Domain Expertise” by Nicholas Kridler of Accretive Health in Chicago.
Hadoop YARN (Yet Another Resource Negotiator) is a resource-management platform responsible for managing compute resources in clusters and using them for scheduling of user applications. YARN was added as part of Hadoop 2.0. Over the past several months of going to conferences like Hadoop Summit, attending big data Meetup groups like LA Big Data Users […]
For this segment of insideBIGDATA Data Science 101, we have a very compelling Google Tech Talk “Building Brains to Understand the World’s Data” presented by Jeff Hawkins, co-founder of Numenta and who also founded Palm and Handspring.