Description
What you’ll learn
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Craft robust deep learning models in computer vision, NLP, and audio without coding.
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Master the experiment flow in H2O Hydrogen Torch, from importing datasets to observing completed experiments.
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Gain practical knowledge in model tuning with grid search and identify optimal hyperparameters.
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Understand the principles of deep learning through hands-on assignments and real-world applications.
Welcome to the H2O Hydrogen Torch Starter Course!
This thrilling course, part of the H2O University and Certification Program, is designed to make cutting-edge AI accessible to everyone, regardless of coding experience. Whether you’re a beginner or a seasoned data scientist, this course offers valuable insights into creating robust models in computer vision, natural language processing (NLP), and audio.
Andreea Turcu, Head of Global Training at H2O ai, guides you through the Hydrogen Torch Starter Course, providing a hands-on learning experience that covers the entire experiment flow. You’ll start by importing and exploring datasets, followed by building and tuning models using grid search to identify optimal hyperparameters. The course emphasizes practical knowledge, allowing you to observe running experiments, explore completed ones, and understand the underlying principles of deep learning.
One of the standout features of this course is its focus on real-world applications. Learn from the best practices of Kaggle competitions and apply these techniques to your projects. By the end of the course, you’ll have the skills to craft sophisticated deep learning models without the need for coding.
Upon completion, you will earn a Certificate of Completion from H2O University, which you can proudly showcase on LinkedIn. This certification not only validates your proficiency in deep learning but also positions you as a frontrunner in the dynamic field of AI and data science. Join us in this exciting journey and unlock the potential of deep learning with H2O Hydrogen Torch.
Who this course is for:
- Data scientists and machine learning enthusiasts looking to expand their knowledge in computer vision, NLP, and audio.
- Professionals seeking to leverage Kaggle best practices in their projects.
- Beginners in deep learning and AI who are eager to learn without the need for coding.
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