Learn essential data preparation techniques for tabular and time series data using H2O Driverless AI. Understand data quality, build datasets, and customize preprocessing with Python.
Ideal for those looking to enhance their machine learning projects with Driverless AI.
What you'll learn
- Data Quality for Machine Learning
Understand why clean and well-structured data is critical for model success.
- Tabular Data Preparation
Learn the basics of supervised and unsupervised learning, tabular formats, and unit of analysis.
- Custom Preprocessing in Driverless AI
See how to prepare datasets, automate tasks, and use Python code for custom preprocessing.
- Time Series Data Basics
Get familiar with time series concepts like date columns, autoregressive models, and multiple series handling.
- Dataset Splitting Techniques
Learn practical strategies to split and prepare time series datasets for model training..
- Best Practices in Data Prep
Understand common challenges and apply solutions to improve model performance.
Course Playlist on YouTube
Introduction to the DataPrep for DriverlessAI Course
Join us for an insightful course on data preparation for machine learning with Driverless AI!
Machine Learning Data Prep Basics
Join Jonathan Farinela, Solutions Engineer at H2O.ai, as he delves into the crucial process of data preparation for machine learning.
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...
Data Exploration Simplified: Guide to Driverless AI Prep
In this video, Jonathan Farinela presents an in-depth guide to preparing and exploring data while utilizing Driverless AI for machine learning task...
Quick Overview: Time Series Data Prep with H2O.ai Driverless AI
Welcome back to our exploration of data preparation with H2O.ai Driverless AI. In this video, we delve into the essential principles and best pract...
