This course 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.
- Import and validate training data
- Transform that data into features
- Train and evaluate your own machine learning model
- Improve the performance of your model
- Data Engineers
- Machine Learning Engineers
- A basic understanding of machine learning concepts
- Some Python experience
Hello, and welcome to “Building a Machine Learning Model”. My name is Daniel Mease and I’ll be taking you through this course. I am a trainer at Cloud Academy with over 20 years of software and web development experience.
This course is intended for:
Machine Learning Engineers
By completing this course, you will learn how to:
Transform that data into features
Train and evaluate your own machine learning model
Improve the performance of your model
The following prerequisites are recommended:
You should already have a basic understanding of machine learning concepts
While not required, it would be useful to have some Python experience
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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.