What to Expect: This tutorial introduces Hugging Face, the leading open-source platform where the machine learning community collaborates on models, datasets, and applications. Best known for its Transformers library for natural language processing, Hugging Face also provides a vibrant ecosystem for sharing, exploring, and deploying machine learning models. You will gain hands-on experience navigating the Hugging Face platform, exploring models that meet specific criteria, and building tools using these models. By the end, you’ll understand how Hugging Face supports modern AI development and how to leverage its tools effectively in your own projects. Key Topics Covered: Introduction to Hugging Face and its role in open-source AI Navigating the Hugging Face ecosystem and model hub Finding and evaluating models based on specific requirements Understanding the platform’s tools, libraries, and community features Hands-on practice: selecting models, working with them in Python, and building simple applications Preparation: Prior experience with Python programming (especially Jupyter Notebooks) is required Ensure Python is installed on your machine; detailed setup instructions and a conda environment file will be provided in advance If you plan to use your own computer, install and activate the conda environment ahead of time Prerequisites: Familiarity with the NumPy library Basic understanding of machine learning and deep learning concepts with some practical experience Recommended Background: If you are new to machine learning, consider attending the preceding tutorials on Machine Learning with Python (Scikit-Learn) and Deep Learning with PyTorch to build a solid foundation. Get ready to explore Hugging Face, experiment with open-source models, and build your own AI-powered applications!