Leverage existing Hadoop cluster with CA

With the Hive ODBC driver and Composable Analytics, users can perform ad-hoc queries on their data living in the HDFS. Hive will take a sql-like query and translate it into map-reduce jobs. These jobs can be chained together within CA applications. In addition, tabular results returned from the query can be fused with data living in other systems.

About
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Lars Fiedler

Lars has comprehensive expertise building large complex software systems, and has served as a Software Engineer at MIT’s Lincoln Laboratory from 2010-2014, where he began developing Composable Analytics. Prior to joining Lincoln Laboratory, Lars worked as a Software Engineer at Microsoft Corporation from 2006 to 2010. Lars received his MS in Computer Science from Georgia Institute of Technology in 2004, and his BS in Computer Science from Georgia Tech in 2003.

Latest posts by Lars Fiedler (see all)

Code Reuse and Modularity in Composable - January 2, 2019
DataOps: Straightforward Data Migration - December 31, 2018
WIX: Scheduling a custom database upgrade to happen After=”InstallSqlData” and Before=”StartServices” - October 24, 2018

KDnuggets

Cartoon: Unsupervised Machine Learning?

New KDnuggets Cartoon looks at one of the hottest directions in Machine Learning and asks "Can Machine Learning be too unsupervised?"

Many Heads Are Better Than One: The Case For Ensemble Learning

While ensembling techniques are notoriously hard to set up, operate, and explain, with the latest modeling, explainability and monitoring tools, they can produce more accurate and stable predictions. And better predictions can be better for business.

Version Control for Data Science: Tracking Machine Learning Models and Datasets

I am a Git god, why do I need another version control system for Machine Learning Projects?

The State of Transfer Learning in NLP

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP organized by Matthew Peters, Swabha Swayamdipta, Thomas Wolf, and Sebastian Ruder. This post highlights key insights and takeaways and provides updates based on recent work.

Clearsense chooses Io-Tahoe’s Smart Data Discovery to navigate healthcare data challenges

Io-Tahoe, a pioneer in Smart Data Discovery and AI-Driven Data Catalog products, has announced that Clearsense, a scalable data platform as a service built for healthcare, has chosen the smart data discovery platform to automatically discover and catalog relationships across immense amounts of medical and clinical data.

There is No Free Lunch in Data Science

There is no such thing as a free lunch in life or data science. Here, we'll explore some science philosophy and discuss the No Free Lunch theorems to find out what they mean for the field of data science.

Ensemble Methods for Machine Learning: AdaBoost

It turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.

A Friendly Introduction to Support Vector Machines

This article explains the Support Vector Machines (SVM) algorithm in an easy way.

Classification vs Prediction

It is important to distinguish prediction and classification. In many decision-making contexts, classification represents a premature decision, because classification combines prediction and decision making and usurps the decision maker in specifying costs of wrong decisions.

Top KDnuggets tweets, Sep 04-10: How #AI will transform #healthcare; 10 Great Python Resources for Aspiring Data Scientists

Python Libraries for Interpretable Machine Learning; How #AI will transform #healthcare (and can it fix US healthcare system?); Building Recommendation System - an overview ; I wasn't getting hired as a Data Scientist. So I sought data on who is.