
Analyze model results and deploy endpoints to test predictions with Google Vertex AI, using metrics like mean absolute error, root mean squared error, and R squared, plus feature importance.
Learn to build a no-code machine learning pipeline with the designer, loading data, converting strings to categoricals, splitting data 80/20, and training a boosted decision tree regression model with evaluation.
Learn to use Azure automated machine learning to preprocess data, select the best regression model for insurance charges (including motor, age, BMI, and children), and deploy a real-time prediction.
If you want to learn machine learning but you feel intimidated by programming or math fundamentals, this course is for you!
You are going to learn how to build projects using six tools that do not require any prior knowledge of computer programming or math! This course was designed for you to create hands-on projects quickly and easily, without a single line of code. It is suitable for beginners and also for students with intermediate or advanced knowledge, who need to increase productivity but at the same time do not have the time to implement code from scratch. You can perform exploratory data analysis, build, train, test and put machine learning models into production with a few clicks!
We are going to cover 6 tools that are widely used for commercial projects: Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure Machine Learning, and Orange! All projects will be developed calmly and step by step, so that you can make the most of the content. There is an exercise along with the solution at the end of each section, so you can practice the steps for each tool! There are more than 30 lectures and 5 hours of videos!