Some Thoughts on Mid-Career Switching Into Data Science Posted by William Vorhies on October 3, 2017 at 7:06am View Blog Summary: If you are mid-career and thinking about switching into data science here are some things to think about in planning your journey. We get lots of inquiries from readers asking for career advice and many […]
This article is several years old, but it’s still very relevant today. I get asked this question all the time by students. Hope you find it helpful. – Ted
(Refreshed Post) Predictive Analytics Made Easy!
Download this free eBook now and see how you can start using Predictive Analytics today to drive business decisions! Read More
(Reposted due to popular demand) Another great video from Josh Wills. Josh is Sr. Director of Data Science at Cloudera and has a gift for making fairly complicated technology explanations very digestible to the novice and intermediary techie.
What I most love about this video is how Josh explains -very clearly – the issue of translating analytics Machine Learning on a large set of data records (many individuals) and making it work well in a “real life” production environment on a single individual (think eCommerce). Watch Video
VIDEO PODCAST | In Episode 5 of this podcast series by Renee Teate of “Becoming a Data Scientist”, she interviews Clare Corthell, founding partner of summer.ai and creator of the Open Source Data Science Masters curriculum, about becoming a data scientist. Read More
Apache Spark’s popularity as part of big data analytics solutions is exploding. Spark is an open-source data analytics cluster computing framework originally developed in the AMPLab at UC Berkeley. Spark fits into the Hadoop open-source community, building on top of the Hadoop Distributed File System (HDFS). However, Spark promises performance up to 100 times faster than Hadoop MapReduce for certain applications…and that’s why you should care!
Spark’s in-memory cluster computing is very well suited to machine learning algorithms. These Videos will give you a nice introduction to Spark, how it’s being used in business and why you should care…Watch Spark Videos…
The challenge of data modeling is to understand how to work with complex data in order to standardize, structure and optimize data to gets accurate insights quickly. Watch this video by Product Manager, Evan Castle of Sisence, to learn everything you need to know about data modeling. Watch Video
VIDEO PODCAST | In Episode 6 and 7 of this podcast series by Renee Teate of “Becoming a Data Scientist”, interviews Erin Shellman and Enda Ridge about how they became Data Scientists and what they do on the job. Read More
Video |Seattle Spark Meetup | Hossein Falaki – Software Engineer and Data Scientist from Databricks introduces us to SparkR and how it integrates the two worlds of Spark and R.
He demonstrates one of the most important use cases of SparkR: exploratory analysis of very large data. Watch Video
Machine learning is a subfield of computer science and artificial intelligence that deals with the construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions (wikipedia).
If you are thinking of doing or becoming a Data Scientist or Advanced Analytics professional, you will absolutely need to master Machine Learning. These 100 Most Popular Talks on Machine Learning topics are a great resource to learn. Review List