A self-study guide for aspiring machine learning practitioners
Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
Ready to start practicing machine learning?
Learn and apply fundamental machine learning concepts with the Crash Course, get real-world experience with the companion Kaggle competition, or visit Learn with Google AI to explore the full library of training resources.
Learn from ML experts at Google
Whether you’re just learning to code or you’re a seasoned machine learning practitioner, you’ll find information and exercises to help you develop your skills and advance your projects.
Prerequisites and Prework
Before beginning Machine Learning Crash Course, do the following:
- If you’re new to machine learning, take Introduction to Machine Learning Problem Framing. This one-hour self-study course teaches you how to identify appropriate problems for machine learning.
- If you are new to NumPy, do the NumPy Ultraquick Tutorial Colab exercise, which provides all the NumPy information you need for this course.
- If you are new to pandas, do the pandas UltraQuick Tutorial Colab exercise, which provides all the pandas information you need for this course.
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Git Free Tutorials For Beginners
- How to login git in windows | Installation of GIT | GitBash login
- Git Basic Commands | Beginners| Upload Your Local Folder To Github
- How To Clone A Repository in Git | Git Clone | Cloning a repository…
- GIT Branches | GIT For Beginners | GIT Pull
- GIT Inspect and Compare | Tracking Path Changes in GIT
- Ignoring Patterns | Rewrite History | GIT Tutorials
- How to logout from git in windows | GIT for beginners
