A machine learning model is a file that is trained to identify multiple relationships in a dataset. Usually, we train a model using a machine learning algorithm and use it for further predictions. Many powerful machine learning models are trained and made available for our use in the form of libraries that can help a data scientist be more productive. So, if you want to learn more about machine learning models that you can use to improve your productivity, then this article is for you. In this article, I’ll walk you through some of the best machine learning models every data scientist should know.
Machine Learning Models Every Data Scientist Should Know
PyCaret is an open-source machine learning library that can automate the entire process of training a machine learning model for you. If you are using PyCaret, you can train machine learning models for classification as well as regression in a few lines of code. Every time you use this model, it provides the performance of all machine learning models on your data so that you can select the best performing model to solve your problem. You can learn all about the PyCaret model here.
AutoTS is another machine learning model that provides the functionality of AutoML for time series forecasting. Anytime you are working on a problem where the output depends on periods such that there is a relationship between the period and the label you want to predict, the AutoTS model can help you a lot. It provides you with the resulting numbers with future dates which is the best feature I like about this machine learning model. You can learn how to use AutoTS for time series forecasting from here.
Many other machine learning models offer the same functionality as PyCaret and AutoTS, but they are still not as good as these models. The best part about these models is that if you use these models on your data, you can also deploy the trained models to production.
So in my opinion, PyCaret and AutoTS are the most important machine learning models that every data scientist should know. As a beginner we use the scikit-learn library in Python which is an industry-standard library. After learning the implementation of machine learning algorithms using scikit-learn, you can learn more about PyCaret and AutoTS models. Hope you liked this article on machine learning models every data scientist should know. Please feel free to ask your valuable questions in the comments section below.