Dec

18

2021

How to deploy Machine Learning Models on IBM Cloud

Laser 18 Dec 2021 10:54 LEARNING » e-learning - Tutorial

How to deploy Machine Learning Models on IBM Cloud
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 248 MB | Duration: 30m

Deploying Machine Learning Models on IBM Cloud
What you'll learn
Learn how to deploy Machine Learning Models on IBM Cloud
Learn to use Watson Machine Learning
Learn to use Watson Studio
Improve Machine Learning Skills in Regression
Create Deployment Space
Register Models
To use several regressors
To visualize predictions
Get predictions From a deployed model
How to Create Training Jobs
How to Create a Notebook
Requirements
Intermediate Python Experience
Basic Machine Learning Experience
Basic Cloud Concepts
Have an active IBM Cloud account
Description
This course is intended for anyone with basic to intermediate experience in machine learning who wants to improve skills in regression but most importantly learn how to deploy machine learning models on IBM Cloud whether they be regressors or classifiers.

By the end of this course you will know how to do that and have a little refresher on data visualization and data analysis. Do not worry if you pay attention in one of the videos I show you how to solve and prevent many problems when registering the model as well as many other things. You will do predictions to evaluate the model and a prediction post deployment. Do not worry about the quizzes if you pay attention to the videos and do the exercises you will easily do well. But most importantly enjoy and have fun learning something new or a minor refreshment on a few things you might have forgotten about. If you want to use another dataset and feel comfortable in doing so feel free and go to kaggle or platform to get your own data set. If that is what you want to do if not feel free then to use this dataset found on Kaggle.
Who this course is for
Those who want to learn to deploy Machine Learning Models on IBM Cloud
Those who want to improve Machine Learning Skills in Regression




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