Summary
This lesson will demonstrate how to build and train your own custom machine learning model from scratch. We cover all steps, including how to set up the environment, how to import and prepare your data, how to build and train the model, as well as how to evaluate its performance and make improvements.
Learning Objectives
- Import and validate training data
- Transform that data into features
- Train and evaluate your own machine learning model
- Improve the performance of your model
Intended Audience
- Data Engineers
- Machine Learning Engineers
Prerequisites
- A basic understanding of machine learning concepts
- Some Python experience
Daniel began his career as a Software Engineer, focusing mostly on web and mobile development. After twenty years of dealing with insufficient training and fragmented documentation, he decided to use his extensive experience to help the next generation of engineers.
Daniel has spent his most recent years designing and running technical classes for both Amazon and Microsoft. Today at Cloud Academy, he is working on building out an extensive Google Cloud training library.
When he isn’t working or tinkering in his home lab, Daniel enjoys BBQing, target shooting, and watching classic movies.