- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 - Dec 3, 2020.
2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.
- Mastering Time Series Analysis with Help From the Experts - Oct 28, 2020.
Read this discussion with the “Time Series” Team at KNIME, answering such classic questions as "how much past is enough past?" others that any practitioner of time series analysis will find useful.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020 - Dec 9, 2019.
As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.
- Text Encoding: A Review - Nov 22, 2019.
We will focus here exactly on that part of the analysis that transforms words into numbers and texts into number vectors: text encoding.
- Time Series Analysis: A Simple Example with KNIME and Spark - Oct 23, 2019.
The task: train and evaluate a simple time series model using a random forest of regression trees and the NYC Yellow taxi dataset.
- Automated Machine Learning: Just How Much? - Sep 5, 2019.
This is an interview between Rosaria Silipo and data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz, asking a few questions on the topic of automated machine learning from their point of view, and some interesting examples of its practical use.
- Anomaly Detection in Predictive Maintenance with Time Series Analysis - Dec 9, 2015.
How can we predict something we have never seen, an event that is not in the historical data? This requires a shift in the analytics perspective! Understand how to standardization the time and perform time series analysis on sensory data.
- Seven Techniques for Data Dimensionality Reduction - May 14, 2015.
Performing data mining with high dimensional data sets. Comparative study of different feature selection techniques like Missing Values Ratio, Low Variance Filter, PCA, Random Forests / Ensemble Trees etc.
- Taming the Internet of Things – KNIME Case Study - Sep 30, 2014.
With increasing interest in the Internet of Things (IoT), see how KNIME can be applied to collect data from IoT sensors, enrich that data, transform it, analyze it, and finally visualize it.
- Where are your users? Geo-localization with KNIME - Apr 28, 2014.
Learn how KNIME can help you improve user understanding through Geo-localization of IP addresses and dynamic visualization. Access free white paper for more details.