Machine Learning Model Deployment with Flask, React & NodeJS | Udemy

Machine Learning Model Deployment with Flask, React & NodeJS | Udemy
English | Size: 1.17 GB
Genre: eLearning

What you’ll learn
Understand the differences between front and back end development
Learn the core information and concepts regarding development
Learn how to integrate a data science model into web development
Deploy data science models as APIs and connect them to the front end

As the world of Data Science progresses, more engineers and professionals need to deploy their work. Whether it’s to test, to obtain user input, or simply to demostrate the model capabilites, it’s becoming fundamental for data professionals to know the best ways to deploy their models. Moreover, being able to deploy models will not only help the data science field become more versatile and in-demand, but it will also benefit the development and ops teams, transforming you into a key player in your workplace.

So, are you ready to jump in and learn how to use the most powerful web development technologies and boost your data science career?

Welcome to the Machine Learning Model Deployment with Flask, React & NodeJS course!

Learn how to take a Data Science or Machine Learning model and deploy it to a Web App and API using some of the most in-demand and popular technologies, including Flask, NodeJS, and ReactJS. Get ready to take a DS model and deploy it in a practical and hands-on manner, simulating a real-world scenario that can be applied to industry practices.

Once you’re done with the course, you’ll have real experience to show hiring managers and stand out among all the other data professionals!

Who this course is for:
Data Scientists who want to take their skills to the next level
ML/AI engineers that want to know how to deploy models
DevOps engineers to understand DS model integrations
Web Developers/Front End Engineers/Back End Engineers
Any one interested in programming or computer science
Software engineers or programmers looking to expand their skill set
In general anyone interested in model deployment and some of the most used libraries in demand today

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