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20 Years of Evolution From Cognitive to Intelligent Communications
It’s been 20 years since the concept of cognitive radio was proposed—radio that could automatically switch from wireless signal to wireless signal, to minimize congestion and allow for more concurrent wireless connections. While this technology has been key in implementing intelligent communications, it’s even more interesting to look at... Read more
3 Signs Your Business is Ready for a Recommendation Engine
Data is in high demand, not just on the business side but for customer-facing solutions as well. When your business can fully integrate data into your customer journey and day to day experience, you become a more valuable tool to that customer. There’s a lot of noise out there;... Read more
Software 2.0 and Snorkel: Beyond Hand-Labeled Data
This ODSC West 2018 talk “Software 2.0 and Snorkel: Beyond Hand-Labeled Data,” presented by Alex Ratner, a Ph.D. student in Computer Science at Stanford University, discusses a new way of effectively programming machine learning systems using what’s called “weaker supervision,” and how it enables domain experts who don’t know... Read more
Wonders in Image Processing with Machine Learning
We discuss some wonders in the field of image processing with machine learning advancements. Image processing can be defined as the technical analysis of an image by using complex algorithms. Here, image is used as the input, where the useful information returns as the output. According to a report,... Read more
Working Towards Planetary Scale Location Insights
Approaches for making geospatial imagery accessible to (geo)data scientists Recent innovations in agile aerospace have created unique offerings in high cadence satellite imagery. While this is of immense interest to imagery analysts, a significant portion of GIS professionals and geo-data scientists work less with raster data (AKA imagery) and... Read more
The Best Machine Learning Research of September 2019
Every month brings its own wave of exciting research, and September was as busy a month as ever for developments in machine learning. To help sort through everything, we’ve compiled our five favorite machine learning research papers of the month, check them out below.  [Related Article: The Best Open... Read more
Using an Embedding Matrix on Tabular Data in R
How would you tackle the prospects of representing a categorical feature, with 100’s of levels, in a model? A first approach may be to create a one-hot encoded matrix representing each level of the feature. The result would be a large and sparse matrix where the majority of the... Read more
3 Common Regression Pitfalls in Business Applications
Regression is a fantastic tool for aiding business decisions. The traditional purpose of a regression model is to find the mean value of a dependent variable given a set of independent variables. In a business, this purpose should be expanded to include the reduction of uncertainty in future events.... Read more
A New Method of Data Mapping – Dimensionality Reduction + Network Theory
When you visit a new place, probably you will rely on a map to guide you from place to place so you could get yourself oriented and help you find the most interesting places. The same happens with data. When you get a new dataset to work with, what... Read more
Generative Adversarial Networks for Finance
Financial instruments like options and futures have been around for more than two centuries. Although they became quite notorious during the 2008 stock market turmoil, they serve a real economic purpose for companies around the world. To explain financial... Read more