Crash Course: Machine Learning Pipeline and API using R

🎓 Course Headline: Build a Dynamic Machine Learning Pipeline with R – A Comprehensive Crash Course for Data Science and Analysis Projects

Course Description:

Hello there, fellow data enthusiasts! 🚀

Embark on an exhilarating journey into the world of predictive analytics with our "Crash Course: Machine Learning Pipeline and API using R." This course, meticulously crafted by data science expert Moritz Müller-Navarra, is designed to provide you with a swift yet comprehensive introduction to building robust predictive models within the powerful R ecosystem.

Why Take This Course?

• Understand Tidymodels: Dive deep into the tidymodels suite of packages, which simplifies and streamlines machine learning workflows in R.
• Master Regression Pipelines: Learn to construct a fully functional automatic regression pipeline tailored to your datasets.
• API Integration: Discover how to expose your model as an API using plumber, making your predictions accessible and scalable.
• Hands-On Learning: Each chapter concludes with practical quizzes to solidify your understanding of the concepts covered.
• Customization & Flexibility: Build a pipeline that can be easily customized and adapted to your specific project needs.
• Immediate Application: Apply what you learn in real-time, creating a versatile tool for data science and analysis projects.

Course Breakdown:

1. Introduction to Tidymodels: Get acquainted with the tidymodels framework and understand its place in the R ecosystem.

   • Learn the core philosophy behind tidymodels.
   • Explore different types of models available in tidymodels.
   • Set up your development environment for working with tidymodels.

2. Building a Regression Pipeline: Follow step-by-step instructions to create a regression pipeline from scratch.

   • Discover key packages and functions within tidymodels.
   • Understand each component of the pipeline, including data preprocessing, model tuning, and evaluation.
   • Learn to train your model using cross-validation.

3. Creating an API with Plumber: Transform your pipeline into a user-friendly API for real-world applications.

   • Understand how to use plumber to create reproducible and scalable APIs.
   • Deploy your API locally or on remote servers.
   • Test your API with different data inputs.

Who Is This Course For?

This course is tailored for:

• Data Science Beginners: If you're new to machine learning in R, this course will provide a solid foundation and guide you through the process of building and deploying a pipeline.
• R & Tidymodels Users: If you're already familiar with R and tidyverse principles but new to machine learning workflows, this course will help you expand your skillset.
• Experienced Analysts: If you're an experienced analyst looking for a way to streamline your machine learning processes, this course will offer efficiency and scalability through pipelines and APIs.

What You Will Gain:

• A solid understanding of how to build predictive models within R using tidymodels.
• The ability to create customizable, automated regression pipelines.
• Experience in deploying your models as accessible APIs using plumber.
• Confidence in applying these techniques to real-world data science and analysis projects.

Join me, Moritz Müller-Navarra, on this exciting adventure into the realm of machine learning with R. Let's turn complex data into actionable insights together! 📊✨

Enroll now and let's get started on building your dynamic Machine Learning Pipeline using R! See you in class. 😊💻

Enroll Now & Level Up Your Data Science Skills!