Automated Machine Learning with AutoGluon Library in Python Course

Discover how to easily automate entire machine learning pipelines with the extremely powerful Autogluon library from AWS.

Welcome to our online course on Autogluon! Are you tired of spending countless hours performing repetitive and time-consuming tasks when it comes to machine learning? Do you want to automate your machine learning tasks and achieve strong predictive performance in your applications with minimal effort? Look no further than Autogluon.

Our comprehensive online course is designed to provide you with the skills and knowledge necessary to use the Autogluon Python library for automating machine learning tasks. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, time series, and tabular data.

Best Seller Course: Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus [2023]

What you’ll learn

• Understand the basics of the Autogluon Python library and its capabilities for automating machine learning tasks.
• Learn how to install and set up the Autogluon Python library in your local environment.
• Develop skills in data preparation and cleaning processes that are critical for successful machine learning outcomes using Autogluon.
• Discover best practices for selecting and configuring machine learning models to achieve optimal results with minimal effort.
• Explore how to use Autogluon to create high-accuracy models for image classification tasks, including object detection, segmentation, and classification.
• Understand how to use Autogluon to perform natural language processing (NLP) tasks such as sentiment analysis.
• Learn how to train and deploy time series models using Autogluon to make accurate predictions for future events or trends.
• Gain hands-on experience in using Autogluon to analyze tabular data and build predictive models for business applications and financial forecasting.

Recommended Course: Complete Machine Learning & Data Science Bootcamp 2023

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