A nice piece which covers the basic concepts of the most used data science algorithms. Not enough to know how to use them, but good for knowing when and why. I often reviewed this level of understanding with executives who were involved in the results. I would also not say 'all', it depends on your domain.
Tags: Algorithms, Decision Tree, Explained, Gradient Boosting, K-nearest neighbors, Machine Learning, Naive Bayes, Regression, SVM
Many machine learning algorithms exits that range from simple to complex in their approach, and together provide a powerful library of tools for analyzing and predicting patterns from data. If you are learning for the first time or reviewing techniques, then these intuitive explanations of the most popular machine learning models will help you kick off the new year with confidence.
By Terence Shin, Data Scientist
Tags: Algorithms, Decision Tree, Explained, Gradient Boosting, K-nearest neighbors, Machine Learning, Naive Bayes, Regression, SVM ... "
No comments:
Post a Comment