Enroll Course: https://www.udemy.com/course/mnist-app/
In the rapidly evolving field of machine learning, countless resources are available for beginners to dive into the world of data science. However, while many individuals may experiment with building simple models, few take the next step to deploy these models as functional applications. This is where the Udemy 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】” comes into play.
This course is designed for data scientists, project managers, and product managers who are eager to understand how to publish machine learning applications using Python and JavaScript. The focus is on practical implementation, guiding learners through the creation of a web application that utilizes a machine learning model trained on the MNIST dataset for handwritten digit recognition.
One of the standout features of this course is its emphasis on MLOps, a crucial aspect of modern machine learning that bridges the gap between model development and deployment. The course teaches you how to export a model trained with Python’s scikit-learn library into ONNX format, allowing for inference in other programming languages, specifically JavaScript. This not only broadens your skill set but also enhances your understanding of how different technologies can work together in the realm of machine learning.
The course is structured to provide hands-on experience. You will go through the steps of building a web application using FastAPI, which is a modern, fast web framework for building APIs with Python. This choice of technology ensures that you are learning industry-relevant skills that are in high demand.
Moreover, the course is continuously updated, with recent additions addressing common issues learners might face, such as setting up the ‘asdf’ environment and troubleshooting errors related to the ‘poetry add’ command. This commitment to keeping the course content fresh and relevant is commendable and adds significant value to the learning experience.
Overall, I highly recommend this course for anyone looking to bridge the gap between theoretical machine learning and practical application. Whether you are a seasoned data scientist or a newcomer to the field, this course will equip you with the tools and knowledge necessary to publish your machine learning models effectively. By the end of the course, you’ll not only have a functional application but also a deeper understanding of the deployment process, which is critical in today’s data-driven landscape.
So if you’re ready to take the plunge into the world of machine learning applications, enroll in “Python と JavaScript による機械学習アプリケーション公開入門【ONNX・Render】” on Udemy and start your journey towards becoming a proficient MLOps practitioner!
Enroll Course: https://www.udemy.com/course/mnist-app/