Enroll Course: https://www.udemy.com/course/mnist-app/
In the rapidly evolving field of machine learning, turning models into accessible web applications is a vital skill. The course titled ‘Python と JavaScript による機械学習アプリケーション公開入門【ONNX・Render】’ offers an excellent introduction for data scientists, PMs, and PDMs who want to learn how to deploy machine learning models on the web effectively. This course guides you through building a web app that leverages a handwritten digit recognition model trained on MNIST, utilizing Python’s scikit-learn to create and export models in ONNX format, and JavaScript to run inference in the browser. Not only does it cover the technical implementation using FastAPI and Git/GitHub for version control, but it also emphasizes deploying your application online via Render, making it accessible to users worldwide. The instructor’s clear explanations and practical approach make complex topics approachable, whether you’re new to MLOps or looking to enhance your deployment skills. If you’re interested in turning your machine learning models into real-world applications, this course is highly recommended. It bridges the gap between model development and deployment, enabling you to showcase your work professionally and practically.
Enroll Course: https://www.udemy.com/course/mnist-app/