[unable to retrieve full-text content]We examine which top tools are “friends”, their Python vs R bias, and which work well with Spark/Hadoop and Deep Learning, and identify an emerging Big Data Deep Learning ecosystem.
Original Post: Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed
The sparklyr package (by RStudio) provides a high-level interface between R and Apache Spark. Among many other things, it allows you to filter and aggregate data in Spark using the dplyr syntax. In Microsoft R Server 9.1, you can now connect to a a Spark session using the sparklyr package as the interface, allowing you to combine the data-preparation capabilities of sparklyr and the data-analysis capabilities of Microsoft R Server in the same environment. In a presentation by at the Spark Summit (embedded below, and you can find the slides here), Ali Zaidi shows how to connect to a Spark session from Microsoft R Server, and use the sparklyr package to extract a data set. He then shows how to build predictive models on this data (specifically, a deep Neural Network and a Boosted Trees classifier). He also shows how…
Original Post: Using sparklyr with Microsoft R Server
[unable to retrieve full-text content]Here is a good list of 75 Big Data terms you can use to impress your father, even if you already bought him a gift.
Original Post: 75 Big Data Terms to Know to Make your Dad Proud
[unable to retrieve full-text content]Data sciences can also be used by HR manager to create several estimates like the investment on talent pool, cost per hire, cost on training, and cost per employee. It provides better techniques for optimization, forecasting, and reporting.
Original Post: How HR Managers Use Data Science to Manage Talent for Their Companies
[unable to retrieve full-text content]TDWI, the leading event for big data, data science & analytics training, comes to Anaheim, Aug 6-11. Save 30% through June 16 with priority code KD30.
Original Post: Latest in Data and Analytics Training, Anaheim – 3 Steps to Convince Your Boss
[unable to retrieve full-text content]Ready to embark on an exciting and in-demand career? Here’s what you need to know about what a data scientist does—and how you can become competitive in this in-demand field.
Original Post: Getting Into Data Science: What You Need to Know
[unable to retrieve full-text content]Top viewed videos on Big Data since 2015 include Big Data use cases in psychographics, sports, politics and data monetisation.
Original Post: Top Recent Big Data videos on YouTube
[unable to retrieve full-text content]Let’s have a look at common quality issues facing Big Data in terms of the key characteristics of Big Data – Volume, Velocity, Variety, Veracity, and Value.
Original Post: Must-Know: What are common data quality issues for Big Data and how to handle them?
[unable to retrieve full-text content]Hadoop Distributed File System (HDFS), and Hbase (Hadoop database) are key components of Big Data ecosystem. This blog explains the difference between HDFS and HBase with real-life use cases where they are best fit.
Original Post: HDFS vs. HBase : All you need to know
[unable to retrieve full-text content]Onalytica’s Big Data Influencer report for 2017 is here. Check out the names and brands that have made the list this year, and get up to speed on the latest happenings in Big Data.
Original Post: Big Data 2017: Top Influencers and Brands