Introduction to Machine Learning
Course summary: Learn about each step in the data science workflow while using Python to clean real-world data and develop a machine learning model. We’ll cover the basics of both supervised and unsupervised models, how to determine the efficacy of your analysis, and how to improve your models. Throughout this course, we’ll see how Domino can speed up experiments and help you share and collaborate with your colleagues.
Duration: Full day
What you’ll learn:
- The basics of supervised and unsupervised machine learning models
- Various metrics for evaluating model performance
- How to improve a model through hyperparameter tuning, feature engineering and cross-validation
- Deploying your model for use in an interactive dashboard