Welcome to this comprehensive tutorial on testing synthetic data using the Train-Synthetic-Test-Real method, where you'll gain valuable insights into evaluating synthetic data quality for your downstream machine-learning models.
Access our state-of-the-art synthetic data generator for free here:
➡️ https://bit.ly/44jGBPr
Here is the publicly available notebook, so you can follow along and experiment with different datasets, models, and synthesizers:
➡️ https://bit.ly/44RdrXl
If you want to know more about how MOSTLY AI's synthetic data generator compares to other generators, read our benchmarking blogpost:
➡️ https://bit.ly/46cNgMa
Here's a high-level overview of what you can expect:
⭐ Introduction to Train-Synthetic-Test-Real - 00:00:00
⭐ The Importance of Synthetic Data Quality - 00:00:05
⭐ Simulating Real-World Machine Learning - 00:00:10
⭐ Setting Up Your Environment - 00:00:14
⭐ Exploring the UCI Adult Income Dataset - 00:02:10
⭐ Generating Synthetic Data with MOSTLY AI - 00:03:06
⭐ Uploading Synthetic Data to Your Notebook - 00:03:54
⭐ Exploring and Comparing the Synthetic Dataset - 00:04:43
⭐ Preparing for Model Training - 00:05:52
⭐ Training and Evaluating the Synthetic Model - 00:06:00
⭐ Training and Evaluating the Real Model - 00:06:50
⭐ Comparing Model Performance - 00:07:46
⭐ The Power of Synthetic Data - 00:07:50
⭐ Experimenting with Your Own Data - 00:08:11
By the end of this tutorial, you'll have a deep understanding of how to harness the power of synthetic data to train your machine-learning models confidently while mitigating privacy risks. Join us as we dive into the world of synthetic data and transform your machine learning projects.
Ready to get started? Let's dive right in and explore the exciting possibilities of Train-Synthetic-Test-Real!