Machine Learning Algorithms for Data Scientists

Machine Learning Algorithms for Data Scientists - 10 Best

June 29, 2018

There is no such thing as the single best machine learning algorithm, there are many ways to approach every problem. And very different data sets can require very different algo's for the best outcome. Choosing between these models is a question of balancing performance, speed and of course avoiding over fitting. I’d say always start out with the more basic models for baseline models and move up the ladder of complexity depending on the task at hand. Sometimes creating a good baseline model is the most difficult part. Anyway, for the sake of creating a list for aspiring data scientists to start from, we have the following:

1. Logistic Regression

2. Linear Regression

3. Classification & Regression Trees

4. Linear Discriminant Analysis

5. K-Nearest Neighbors

6. Naive Bayes

7. Support Vector Machines

8. Learning Vector Quantization

9. Boosting and Adaboost

10. Bagging and Random Forest

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