Summary

In this chapter, we learned about the available algorithms for each library in Optimus to handle ML. We saw about train-test split evaluation and when to use it.

We also learned about different training models such as linear regression, logistic regression, k-means, random forest, and PCA.

Finally, we learned how to load and save those models for further use or deployment.

In the next chapter, we will learn about how to use the natural language function available in Optimus.