This beginner-friendly course introduces you to H2O Hydrogen Torch, a no-code platform designed for building deep learning models in areas like image classification, text analysis, and audio processing. Learn how to navigate the interface, run experiments, and apply best practices drawn from real-world use cases.
What you'll learn
- No-Code Deep Learning
Understand deep learning fundamentals through a visual, no-code interface using H2O Hydrogen Torch.
- Experiment Flow Navigation
Learn the full experiment lifecycle—from data import to observing results.
- Multi-Modal Problem Support
Explore how to build models across text, images, 3D images, and video data.
- Model Tuning Techniques
Apply grid search and adjust hyperparameters for better model performance.
- Platform Onboarding & Setup
Get familiar with platform setup, key features, and launching your first experiment.
- Hands-On Learning & Certification
Engage in interactive assignments and earn certification upon course completion.
Course Playlist on YouTube
H2O Hydrogen Torch Starter Course TEASER
🔥 Welcome to the H2O Hydrogen Torch Starter Course! 🔥
1. H2O Hydrogen Torch: Deep Learning Made Easy!
🚀 Immerse yourself in the realm of deep learning with the H2O Hydrogen Torch!
2. Empowering Deep Learning with Simplicity and Precision
Explore H2O Hydrogen Torch, an advanced tool that streamlines deep learning model training with predefined hyperparameters and methods inspired by ...
3. Diverse Challenges, One Solution: H2O Hydrogen Torch
H2O Hydrogen Torch is a versatile tool for data scientists, enabling them to address a wide range of challenges in computer vision, natural languag...
Getting Started with H2O.ai Aquarium
This video will guide you through accessing and using Aquarium Labs, which offers a hands-on, practical learning experience by replicating H2O.ai’s...
4. Quick Setup Guide: Launching H2O Hydrogen Torch
🚀 Ready to dive into deep learning? Join us for a rapid setup guide on using H2O Hydrogen Torch in the H2O AI Cloud (HAIC). Learn how to create in...
5. Mastering H2O Hydrogen Torch in 3 Simple Steps
🚀 Master the power of H2O Hydrogen Torch with our step-by-step guide!
6. Effortless Experimentation: Exploring H2O Hydrogen Torch's Interface
In this video you will give you a quick guide to explore the interface of H2O Hydrogen Torch! Let's dive together into the application's functional...
7. Dive into H2O Hydrogen Torch: Crafting Image Regression Models
Our focus for this model will be to craft an image regression model predicting Brazilian Real (R$) coins. If you are interested to learn the best d...
7.1. Deep Dive into Coins: Hydrogen Torch Exploration of the Dataset!
🌟 Welcome to our tutorial on using the preprocessed Coins image regression dataset with H2O Hydrogen Torch! 🌟
7.2. Building and Evaluating a Model with H2O Hydrogen Torch
👋 Welcome, deep learning enthusiasts! In this tutorial, we'll continue our work on the Coins Image Regression dataset and start building a model t...
7.3. From Zero to Hero: Image Regression Model Building in H2O Hydrogen Torch
🚀 Welcome to our H2O Hydrogen Torch tutorial on building your first image regression model! 🖼️ In this video, we'll guide you through the process...
7.4. Exploring Model Performance of Hydrogen Torch in Real-Time!
🌟 Ready for a journey into the heart of cutting-edge deep learning modeling?
7.5. View completed experiment in Hydrogen Torch, Analyze, and Optimize!
Welcome back! Here are some of the practical steps that you will learn in this tutorial: 1. "View experiments" in the H2O Hydrogen Torch menu.
8. From Start to Spark: Key Moments in Our H2O Hydrogen Torch Debut
In the initial phases of our learning journey, we delved into H2O Hydrogen Torch, initiating our first experiment. Here's a brief overview:
9. Optimizing Image Learning: Grid Search in H2O Hydrogen Torch
In this course, we delve into practical grid search techniques, emphasizing image metric learning for assessing bicycle image similarity.
9.1. Effortless Import with H2O Hydrogen Torch: Stanford Bicycle Dataset
In this tutorial, we'll quickly import and explore the Stanford bicycle image metric learning dataset in H2O Hydrogen Torch.
9.2. Image Learning Made Simple: Default Model Construction in H2O Hydrogen Torch
In this video, we'll be building an image metric learning model with default hyperparameters using H2O Hydrogen Torch. Let's walk through the key s...
9.3. Navigating Results: Assessing Model Performance and Default Settings with H2O Hydrogen Torch
Welcome back! In this session, we'll dive into the outcomes of your completed experiment. We'll explore how the model is assessed, understand the s...
9.4. H2O Hydrogen Torch Grid Search: Your Key to Model Optimization
In machine learning, hyperparameters are pre-set configurations influencing a model's behavior (e.g., learning rate).
9.5. Exploring Optimal Configurations: A Guide to Model Enhancement with H2O Hydrogen Torch
In this video, we focus on tuning the backbone architecture, exploring various embedding sizes, and fine-tuning learning rates.
9.6. Comparing Wins in H2O Hydrogen Torch: Finding the Top-Performing Model
Welcome back! Now, the H2O Hydrogen Torch experiments are complete, and in this session we will found our top-performing model based on mean avera...
9.7. Optimize with H2O Hydrogen Torch for peak model performance
📈 In this video you will learn how to enhance your initial model by leveraging settings from the best-performing model.
10. Next Steps
Congratulations on completing the H2O Hydrogen Torch Starter Course!
