Ensemble Methods in One Picture
Ensemble methods take several machine learning techniques and combine them into one predictive model. It is a two step process: Generate the Base Learners: Choose any c...
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All About Using Jupyter Notebooks and Google Colab
Introduction Interactive notebooks are experiencing a rise in popularity. How do we know? They’re replacing PowerPoint in presentations, shared around organizations, an...
Now that We’ve Got AI What do We do with It?
Summary: Whether you’re a data scientist building an implementation case to present to executives or a non-data scientist leader trying to figure this out there’s a...
5 Key Best Practices for Successfully Adopting and Implementing Machine Learning in an Organization
Machine Learning (ML) has been among the top strategies for almost every organization – whoever adopts the new methodology early and quickly establishes the corpora...
Logistic Regression in One Picture
Logistic regression is regressing data to a line (i.e. finding an average of sorts) so you can fit data to a particular equation and make predictions for your data. This ...
Efficient Tuning of Online Systems Using Bayesian Optimization
This article, written by the Facebook research team, was written by Ben Letham, Brian Karrer, Guilherme Ottoni and Eytan Bakshy. It features some of the techniques used b...
K-nn Clustering Explained in One Picture
This is a simple overview of the k-NN process. Perhaps the most challenging step is finding a k that’s “just right”. The square root of n can put you i...
Is Robotic Process Automation (RPA) Really AI?
Summary: Based on a McKinsey study we reported that 47% of companies had at least one AI/ML implementation in place. Looking back at the data and the dominance of RPA...
Determining Sample Size in One Picture
Determining sample sizes is a challenging undertaking. For simplicity, I’ve limited this picture to the one of the most common testing situation: testing for differ...
15 Great Articles about Bayesian Methods and Networks
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...