Neural Networks: Is Meta-learning the New Black?
I’ve written several times about how the “economies of learning” are more powerful than the “economies of scale”. Through a continuous learning and refinement...
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Machine Learning in Agriculture: Applications and Techniques
Recently we have discussed the emerging concept of smart farming that makes agriculture more efficient and effective with the help of high-precision algorithms. The mecha...
Comparing Model Evaluation Techniques Part 1: Statistical Tools & Tests
Evaluating a model is just as important as creating the model in the first place. Even if you use the most statistically sound tools to create your model, the end result ...
Alternatives to R-squared (with pluses and minuses)
R-squared can help you answer the question “How does my model perform, compared to a naive model?”. However, r2 is far from a perfect tool. Probably the mai...
Forecasting through ARIMA Modeling using R – Step-by-step Guide
This article was written by Roopam Upadhyay. This article is a continuation of our manufacturing case study example to forecast tractor sales through time series and ARI...
Deep learning: the final frontier for signal processing and time series analysis?
This article was written by Alexandr Honchar. People use deep learning almost for everything today, and the “sexiest” areas of applications are computer vision, natur...
Adversarial Attacks on Deep Neural Networks: an Overview
Introduction Deep Neural Networks are highly expressive machine learning networks that have been around for many decades. In 2012, with gains in computing power and impro...
Cross-Validation: Concept and Example in R
This article was written by Sondos Atwi. In Machine Learning, Cross-validation is a resampling method used for model evaluation to avoid testing a model on the same dat...
Significance Level vs Confidence level vs Confidence Interval
You may have figured out already that statistics isn’t exactly a science. Lots of terms are open to interpretation, and sometimes there are many words that mean the...
A Comprehensive Guide to Stochastic Gradient Descent Algorithms
This article was written by Giuseppe Bonaccorso. Stochastic Gradient Descent (SGD) is a very powerful technique, currently employed to optimize all deep learning model...