- 4 Most Popular Alternative Data Sources Explained - Jul 2, 2019.
Alternative data is the new game changer. To start with alternative data, people might even wonder from where you can get hold of alternative data that can give such a competitive advantage. This post details 4 alternative data sources that you can exploit to the fullest.
- Charles River Analytics: Software Engineer – Physiological Sensing and Machine Learning - Jul 20, 2018.
Seeking an engineer experienced in signal processing, time series analysis, and/or machine learning who can contribute to the development of software aimed at interpreting information provided by wearable devices such as Fitbits and iWatches.
- The Future of Map-Making is Open and Powered by Sensors and AI - Jul 13, 2018.
This article investigates the future of map-making and the role of Sensors, Artificial Intelligence and Machine Learning within that.
- Apple: Jr. Instrumentation Data Scientist – Exploratory Design Group - Jul 12, 2018.
Seeking an enthusiastic engineer to collaborate with a R&D team of developing a new generation of bio-sensing technologies. The ideal candidate will have experience applying data analysis techniques to understand complex measurements.
- Edge Analytics – What, Why, When, Who, Where, How? - Oct 11, 2017.
Edge analytics is the collection, processing, and analysis of data at the edge of a network either at or close to a sensor, a network switch or some other connected device.
- Internet of Things Tutorial: IoT Devices and the Semantic Sensor Web - Jan 30, 2017.
IoT applications have to collect and analyze information from multiple heterogeneous objects. Dealing with multiple sensors and internet connected objects, at multiple levels, requires attention. Read on to find out more.
- Internet of Things Tutorial: WSN and RFID – The Forerunners - Jan 6, 2017.
WSN and RFID are key to understanding more complex IoT concepts and technologies, but also the structure of non-trivial IoT systems, which are very likely to comprise RFID or WSN components.
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- Internet of Things (IoT) Challenge: The Sensor That Cried Wolf - Dec 23, 2016.
William Schmarzo, the "Dean of Big Data," shares a personal story that identifies a tangible issue related to technology in general, and which carries an important message for the Internet of Things (IoT) in particular.
- What the Next Generation of IoT Sensors Have in Store - Jul 19, 2016.
This post is an overview of some of the next-generation IoT sensors, and what they could mean for our future.
- CrowdSignals.io, Building Big Mobile Social Sensor dataset - Mar 25, 2016.
CrowdSignals.io a crowdfunding campaign to generate the largest mobile and sensor dataset available to the Data Science community for use in research and product development.
- Data Science of IoT: Sensor fusion and Kalman filters, Part 2 - Nov 9, 2015.
The second part of this tutorial examines use of Kalman filters to determine context for IoT systems, which helps to combine uncertain measurements in a multi-sensor system to accurately and dynamically understand the physical world.
- Data Science of IoT: Sensor fusion and Kalman filters, Part 1 - Oct 29, 2015.
The Kalman filter has numerous applications, including IoT and Sensor fusion, which helps to determine the State of an IoT based computing system based on sensor input.
- Interview: Amit Sheth, Kno.e.sis on Deriving Actionable Insights from Social Data - Jan 15, 2015.
We discuss Twitris—a tool for collective social intelligence, challenges in using social data to get actionable insights during emergency situations, managing Data Variety, and entrepreneurship.
- Big Data Top Trends in 2015 - Nov 28, 2014.
Big Data may bring increased usage of in-memory databases, data democratization, sensor data, customer and HR analytics, and big data-driven corporate insights in 2015, according to Josie King of Innovation Enterprise.
- Analatom: Artificial Intelligence / Data Mining Engineer (US Permanent Residency or Citizenship Required) - Oct 12, 2014.
Work with large data sets, complex algorithms, and team members from a variety of specialties to solve hard problems. Support a range of clients, including front-line analysts, researchers, and senior leadership.