Controlled Experiments in Machine Learning

Systematic experimentation is a key part of applied machine learning. Given the complexity of machine learning methods, they resist formal analysis methods. Therefore, we must learn about the behavior of algorithms on our specific problems empirically. We do this using controlled experiments. In this tutorial,…

Statistical Significance Tests for Comparing Machine Learning Algorithms

Comparing machine learning methods and selecting a final model is a common operation in applied machine learning. Models are commonly evaluated using resampling methods like k-fold cross-validation from which mean skill scores are calculated and compared directly. Although simple, this approach can be misleading as…

AI Making Real-Time Analytics More Real, Driving High Value – AI Trends

We’ve come a long way with analytics in recent years, in which data is applied against algorithms or analytics engines to determine what it may mean to the business. Lately, there’s been a lot of progress with real-time analytics, especially when applied against streaming data…

A Gentle Introduction to the Chi-Squared Test for Machine Learning

A common problem in applied machine learning is determining whether input features are relevant to the outcome to be predicted. This is the problem of feature selection. In the case of classification problems where input variables are also categorical, we can use statistical tests to…

A Gentle Introduction to Statistical Sampling and Resampling

Data is the currency of applied machine learning. Therefore, it is important that it is both collected and used effectively. Data sampling refers to statistical methods for selecting observations from the domain with the objective of estimating a population parameter. Whereas data resampling refers to…

Introduction to Nonparametric Statistical Significance Tests in Python

In applied machine learning, we often need to determine whether two data samples have the same or different distributions. We can answer this question using statistical significance tests that can quantify the likelihood that the samples have the same distribution. If the data does not…

Statistics Books for Machine Learning

Statistical methods are used at each step in an applied machine learning project. This means it is important to have a strong grasp of the fundamentals of the key findings from statistics and a working knowledge of relevant statistical methods. Unfortunately, statistics is not covered…

Total to Develop Artificial Intelligence Solutions with Google Cloud

… an agreement to jointly develop  artificial intelligence (A.I.) solutions applied to … geoscience expertise and Google’s artificial intelligence skills will ensure the project … .”   Artificial Intelligence Applied to Exploration & Production at Total   Total started applying artificial intelligence … VISIT THE…

Artificial intelligence technology shows signs of maturing, says Google AI expert

Artificial intelligence and machine learning have long …  (pictured), technical director of applied artificial intelligence at Google, has been involved … . They discussed the evolution of artificial intelligence from concept to productization. At … VISIT THE SOURCE ARTICLE Author: