Gartner Advanced Analytics Magic Quadrant Updates

William Vorhies summarizes the changes to the Gartner Advanced Analytics magic quadrant:

The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is just out and once again there are big changes in the leaderboard.  Say what you will about our profession but as a platform developer you certainly can’t rest on your laurels.  Some traditional leaders have fallen (SAS, KNIME, H2Oai, IBM) and some challengers have risen (Alteryx, TIBCO, RapidMiner).

Databricks is making a big push and there’s more movement than usual in this year’s chart. Check it out.

Related Posts

Monte Carlo Simulation in Python

Kristian Larsen has a couple of posts on Monte Carlo style simulation in Python. First up is a post which covers how to generate data from different distributions: One method that is very useful for data scientist/data analysts in order to validate methods or data is Monte Carlo simulation. In this article, you learn how […]

Read More

Hyperparameter Tuning with MLflow

Joseph Bradley shows how you can perform hyperparameter tuning of an MLlib model with MLflow: Apache Spark MLlib users often tune hyperparameters using MLlib’s built-in tools CrossValidator and TrainValidationSplit.  These use grid search to try out a user-specified set of hyperparameter values; see the Spark docs on tuning for more info. Databricks Runtime 5.3 and 5.3 ML and above support […]

Read More

Categories

February 2019
MTWTFSS
« Jan Mar »
 123
45678910
11121314151617
18192021222324
25262728