Knowledge graphs are network graphs that link related concepts and properties together to create a form of inferencing engine, with knowledge engineering being the programming aspect of graph usage. Explore how knowledge graphs are created and queried, how they are used as part of a broader form of enterprise metadata management, and how they tie into ML and the IoT.
The continued evolution of technology has changed our lives in more profound ways than we’d ever been able to imagine. Think about it — we… Read More »Machine Learning: How it is Transforming the Education Sector
Rationalizing the effort of our intensive care staff by predicting patient condition indicators in real time is a challenge because of an impressive number of… Read More »Horowitz Index Day-Ahead Change Prediction in Real Time
A few years ago, it was extremely uncommon to retrain a machine learning model with new observations systematically. This was mostly because the model retraining… Read More »When Should a Machine Learning Model Be Retrained?
A summary of the book “Introduction to Statistical Learning” in jupyter notebooks Whenever someone asks me “How to get started in data science?”, I usually… Read More »Statistical Machine Learning in Python
Introduction Almost every machine learning algorithm comes with a large number of settings that we, the machine learning researchers and practitioners, need to specify. These… Read More »Cross-validation and hyperparameter tuning
Interesting picture summarizing several types of techniques used in machine learning, contrasting unsupervised learning with unsupervised learning and reinforcement learning. The difference between supervised and… Read More »Machine Learning with Applications in One Picture
This article was written on Graymatter. Let start at the beginning; back in the 50’s we dreamt about robots making our tea (AI) and what… Read More »A simple guide to AI, Machine Learning and Deep Learning
This article was written by Fjodor Van Veen. With new neural network architectures popping up every now and then, it’s hard to keep track of them all.… Read More »The Neural Network Zoo
It is always hard to find a proper model to forecast time series data. One of the reasons is that models that use time-series data… Read More »Time Series Forecasting: KNN vs. ARIMA
Scaling AI with Dynamic Inference Paths in Neural Networks Introduction IBM Research, with the help of the University of Texas Austin and the University of… Read More »Blockdrop to Accelerate Neural Network training by IBM Research
