Databricks AutoML is an important step towards the democratization of machine learning. AutoML makes it easy for anyone to build and train robust models with little to no code. In this course, Automate Machine Learning Using Databricks AutoML, you will be introduced to the basic concepts of Databricks AutoML. First, you will see how AutoML automates every step of the machine learning process from data preparation, and data preprocessing to model training and evaluation. Next, you will first train regression and classification models using the AutoML user interface to configure your model training, and you can configure settings to impute missing values, choose model frameworks and evaluate models. Then, you will learn to use the AutoML Python API to train regression and classification models. The Python API offers simple regress() and classify() functions which you can configure using input parameters. Finally, you will work with time series datasets and train forecasting models using both the AutoML UI and the AutoML Python API. When you are finished with this course you will be able to confidently use AutoML to train regression, classification, and forecasting models and deploy them to production.
Author Name: Janani Ravi
Author Description:
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing … more