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Web Scraping News Articles in Python
This article is the second of a series in which I will cover the whole process of developing a machine learning project. If you have not read the first one, I strongly encourage you to do it here. The project involves the creation of a real-time web application that gathers data from several newspapers... Read more
Balancing Interpretability and Predictive Power with Cubist Models in R
Machine learning models are powerful tools that do well in their purpose of prediction. In many business applications, the power of these models is quite beneficial. With any application of a machine learning model, the process to choosing which model involves determining the model that performs best across a... Read more
Creativity Inspired Zero-shot Learning
Zero-shot learning (ZSL) aims at understanding unseen categories with no training examples from class-level descriptions. To improve the discriminative power of zero-shot learning, we model the visual learning process of unseen categories with inspiration from the psychology of human creativity for producing novel art. We relate ZSL to human... Read more
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
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
RAPIDS Forest Inference Library: Prediction at 100 Million Rows per Second
Random forests (RF) and gradient-boosted decision trees (GBDTs) have become workhorse models of applied machine learning. XGBoost and LightGBM, popular packages implementing GBDT models, consistently rank among the most commonly used tools by data scientists on the Kaggle platform. We see similar interest in forest-based models in industry, where... Read more
Automating Image Annotation with MAX
This blogpost introduces a use-case example to automate image annotation with MAX (Model Asset Exchange). To learn more about how our deep learning models are created, containerized, and deployed to production, come join our training at ODSC West 2019: Deploying Deep Learning Models as Microservices.  Introduction The Model Asset Exchange... Read more