autosklearn
14 hours (usually 2 days including breaks)
Audience
Auto-sklearn is a Python package built around the scikit-learn machine learning library. It automatically searches for the right learning algorithm for a new machine learning dataset and optimizes its parameters.
This instructor-led, live training (onsite or remote) is aimed at machine learning practitioners who wish to use Auto-sklearn to automate the process of selecting and optimizing a machine learning model.
By the end of this training, participants will be able to:
Format of the Course
Course Customization Options
Introduction
Setting up a Working Environment
Installing Auto-sklearn
Anatomy of a Standard Machine Learning Workflow
How Auto-sklearn Automates the Machine Learning Workflow
Searching for the Best Neural Network Architecture with NAS (Neural Architecture Search)
Case Study: AutoML with Auto-sklearn
Downloading a Dataset
Building a Machine Learning Model
Training and Testing the Model
Tuning the Hyperparameters
Building, Training, and Testing Additional Models
Tweaking the Hyperparameters to Improve Accuracy
Configuring Auto-sklearn for Deep Learning Models
Troubleshooting
Summary and Conclusion
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