RapidMiner is a software platform developed by the company of the same name that provides an integrated environment for machine learning, data mining, text mining, predictive analytics and business analytics.
Search Results for: text mining
How Can You Effectively Select the Correct Language Model to Align with Your Business Needs and Goals?
August 18, 2023 by 1 Comment
In this contribute article, Garry M. Paxinos, CTO of netTALK CONNECT, believes that not all language models are the same: How can you effectively select the right language model that aligns with your business needs and goals? What capabilities cannot go unnoticed when analyzing language models?
Video Highlights: Maching Learning in R – Three Reasons to Use tidymodels
July 5, 2020 by Leave a Comment
The following video presentation comes from my favorite Meetup group “LA R users group”, a 2,200+ member group that puts on some amazing virtual presentations. This talk centers around that fact that modeling and machine learning in R involve a bewildering array of heterogeneous packages, and establishing good statistical practice is challenging in any language. The tidymodels collection of packages offers a consistent, flexible framework for your modeling and machine learning work to address these problems.
Interview: Tammy Bilitzky, CIO of DCL
May 30, 2018 by 2 Comments
I recently caught up with Tammy Bilitzky, CIO of DCL, to do a deep dive into how her company utilizes state-of-the-art technologies like machine learning, AI, deep learning and NLP to make DCL’s products competitive. Tammy is responsible for managing DCL’s technology department, continuing its focus on resilient, high-quality, and innovative products, while helping to grow the organization.
The Digital Art of Detecting Fraud
August 3, 2017 by Leave a Comment
In this special guest feature, Christopher Hillman, Principal Data Scientist in the International Advanced Analytics team at Teradata, discusses the significant progress being made in the area of fraud detection through use of machine learning by providing new insights into existing problems.
Is Data Vault Modeling a Good Choice for Your Organization?
July 28, 2017 by 1 Comment
In this special guest feature, Moshe Kranc, CTO at Ness Digital Engineering, discusses data vault modeling and the key benefit of data vault architecture is that it has a design that is flexible and adaptable to meet the changing needs of an enterprise.
Five Steps to Tackling Big Data with Natural Language Processing
July 10, 2017 by Leave a Comment
In this special guest feature, Paul Nelson, Chief Architect at Search Technologies, discusses his top 5 essential steps for tackling a Big Data project using Natural Language Processing (NLP) and also how NLP tools and techniques help businesses process, analyze, and understand all of this data in order to operate effectively and proactively.
“Above the Trend Line” – Your Industry Rumor Central for 4/4/2017
April 4, 2017 by Leave a Comment
Above the Trend Line: machine learning industry rumor central, is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.
“Above the Trend Line” – Your Industry Rumor Central for 2/27/2017
February 27, 2017 by Leave a Comment
Above the Trend Line: machine learning industry rumor central, is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.
Bigger is Better: Why Enterprise Analytics Needs Scale
February 21, 2017 by Leave a Comment
In this special guest feature, Andrew Pease, Principal Business Solutions Manager at SAS, discusses why enterprise analytics must incorporate scale and its relation to speed and innovation within an organization.
