- Industry Predictions: AI, Machine Learning, Analytics & Data Science Main Developments in 2018 and Key Trends for 2019 - Dec 18, 2018.
This is a collection of data science, machine learning, analytics, and AI predictions for next year from a number of top industry organizations. See what the insiders feel is on the horizon for 2019!
2019 Predictions, AI, Analytics, Data Science, Domino, dotData, Figure Eight, Industry, Knime, Machine Learning, MapR, MathWorks, OpenText, ParallelM, Salesforce, Splice Machine, Splunk
- Industry Predictions: Main AI, Big Data, Data Science Developments in 2017 and Trends for 2018 - Dec 19, 2017.
Here is a treasure trove of analysis and predictions from 17 leading companies in AI, Big Data, Data Science, and Machine Learning: What happened in 2017 and what will 2018 bring?
2018 Predictions, AtScale, Dataiku, Hype, IBM, Industry, Kaggle, Knime, MathWorks, Predictions, RapidMiner, Splice Machine, Splunk
- Evaluating HTAP Databases for Machine Learning Applications - Nov 2, 2016.
Businesses are producing a greater number of intelligent applications; which traditional databases are unable to support. A new class of databases, Hybrid Transactional and Analytical Processing (HTAP) databases, offers a variety of capabilities with specific strengths and weaknesses to consider. This article aims to give application developers and data scientists a better understanding of the HTAP database ecosystem so they can make the right choice for their intelligent application.
Pages: 1 2
Big Data, Data Processing, HTAP, Oracle, SAP, Splice Machine, SQL
- 5 Reasons Machine Learning Applications Need a Better Lambda Architecture - Jun 2, 2016.
The Lambda Architecture enables a continuous processing of real-time data. It is a painful process that gets the job done, but at a great cost. Here is a simplified solution called as Lambda-R (ƛ-R) for the Relational Lambda.
Applications, Lambda Architecture, Machine Learning, Monte Zweben, Splice Machine