Hyperparameter Tuning with Neural Network Intelligence
38 ratings

3,008 already enrolled
Create and run hyperparameter tuning experiments using NNI
38 ratings
3,008 already enrolled
Create and run hyperparameter tuning experiments using NNI
In this 2-hour long guided project, we will learn the basics of using Microsoft's Neural Network Intelligence (NNI) toolkit and will use it to run a Hyperparameter tuning experiment on a Neural Network. NNI is an open source, AutoML toolkit created by Microsoft which can help machine learning practitioners automate Feature engineering, Hyperparameter tuning, Neural Architecture search and Model compression. In this guided project, we are going to take a look at using NNI to perform hyperparameter tuning. Please note that we are going to learn to use the NNI toolkit for hyperparameter tuning, and are not going to implement the tuning algorithms ourselves. We will use the popular MNIST dataset and train a simple Neural Network to learn to classify images of hand-written digits from the dataset. Once a basic script is in place, we will use the NNI toolkit to run a hyperparameter tuning experiment to find optimal values for batch size, learning rate, choice of activation function for the hidden layer, number of hidden units for the hidden layer, and dropout rate for the dropout layer. To be able to complete this project successfully, you should be familiar with the Python programming language. You should also be familiar with Neural Networks, TensorFlow and Keras. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Deep Learning
Artificial Neural Network
Machine Learning
automl
hyperparameter tuning
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction
Rhyme Interface
Load Data
Create Model
Model Training
Hyperparameter Search Space
Creating and Running the Experiment
Final Results
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
by TL
Jul 30, 2022Thank you. This helped me gain a stronger comprehension of machine learning concepts I'd learned from other courses by creating an intuitive local webpage desgined to view the results of my models.
by TL
Oct 9, 2020Great Instructor. Great project. I am looking forward to other projects that explore NNI capabilities
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
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At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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