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Creating a Scalable Machine Learning Pipeline
Duration: 7h56m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 3.89 GB
Genre: eLearning | Language: English
Gather Data, Train Deep Learning Models, Evaluate, Use & Deploy, Review, and Update Machine Learning Models
What you'll learn
The course will focus on what to build once you have a Machine Learning Model. Allowing you to improve and monitor your deep learning model in production.
Tensorflow Js, Firebase, Material UI, React
Requirements
Have some familiarity with Javascript, HTML and CSS
No Machine Learning experience needed
Description
I show you you everything you need to start using your tflite and tensorflow.js machine learning models in production. Create a website that allows users to upload images, get predictions from your custom machine learning model and review the performance of the model in real time.
Whether you already have a computer vision model or not I show you how to easily create one and ultimately use and deploy it to production. Learn how to use your own custom models with tensorflow.js, allowing users to upload images and get predictions back on that image.
We create an entire pipeline that allows you to improve and monitor your machine learning model's over time. Allow users to upload new images for predictions, saving those predictions and then using the new images as training data to improve our custom models performance.
Who this course is for:
Software Developers, Data Scientists, Machine Learners, Entrepreneurs
Download link:
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