Support Vector Machines with scikit-learn

Delve into the powerful world of Support Vector Machines (SVMs) with scikit-learn through this hands-on project on Rhyme. In under 2 hours, you will gain a deep understanding of SVM functioning, intuition, and practical application.

• Gain insight into the theory behind SVMs
• Learn to build SVM models with scikit-learn to classify both linear and non-linear data
• Understand the strengths and limitations of SVMs for various classification tasks
• Develop an SVM-based facial recognition model, applying your newfound knowledge in a practical setting

By the end of the project, you will be equipped with the skills to apply SVMs using Python and scikit-learn to your own classification tasks, including building a simple facial recognition model. With instant access to a pre-configured cloud desktop containing all necessary software and data, you can focus solely on the learning process, making this project ideal for learners in the North America region.