Develop state-of-the-art machine learning models with just a few lines of code!
If you want to build efficient models using the open-source Auto-Keras library, then this course is perfect for you. It will teach you how to use Auto-Keras to build custom machine learning and AI models effectively, even with limited machine Learning knowledge.
You will learn how to train a network automatically and evaluate it using Auto-Keras. You will begin by installing Auto-Keras and using it to implement basic algorithms. You will then train more advanced models as you progress to state-of-the-art techniques.
By the end of the course, you will be confident about using Auto-Keras to build custom machine learning models for your organization.
All the related code files are placed on GitHub repository at: https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-Auto-Keras
- Learn how to leverage the power of auto machine learning by applying Auto-Keras to real-world problems and data sets
- Find out how Auto-Keras can help you obtain close to state-of-the-art performance on ML tasks with only a few lines of code
- Explore time, resource, and development quality benefits that Auto-Keras can bring to your organization
What you will Learn:
- Visualize how Auto-Keras works by learning some of its best-performing architectures
- Achieve state-of-the-art Convolutional Neural Network performance in realistic scenarios and with very little development time
- Improve performance on text-based tasks involving classification and regression
- Obtain production-ready models with Auto-Keras on sentiment analysis tasks
- Leverage pre-trained models in Auto-Keras to save time by writing less code and by not doing any model training
- Generate your own datasets in order to estimate how well Auto-Keras performs in complex conditions
- Learn how to build and make predictions and your own data sets
- Learn the basics of deploying a model
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