Synthetic Data Generation with MOSTLY AI

Join Nick from MOSTLY AI as he guides us through an insightful demo of MOSTLY AI's synthetic data platform, showcasing the process of creating statistically representative synthetic data. This comprehensive tutorial dives into the world of synthetic data generation, and all the useful features you need for next level machine learning tasks, offering privacy-secure and highly accurate synthetic datasets together with advanced options, like data upsampling.

In this video, you'll discover:

➡️ How to utilize the MOSTLY AI platform to generate synthetic data from sample datasets.
➡️ The process of configuring data settings and generating specific volumes of synthetic data.
➡️ A walkthrough of MOSTLY AI's QA report for evaluating the accuracy and privacy metrics of synthetic data.
➡️ Strategies for rebalancing datasets to enhance machine learning models and avoid bias.
➡️ The benefits of using synthetic data for data science teams, including privacy-safe augmentation, upsampling, data imputation, and data experimentation.

Whether you're a data science professional or enthusiast, this video provides a deep understanding of how to leverage synthetic data in your projects. Get ready to explore the intricacies of synthetic data modeling and how it can revolutionize your approach to data analysis and machine learning.

Key moments:

0:00: Introduction to the MOSTLY AI Synthetic Data Platform
0:07: Generating Synthetic Data
1:03: Training Settings for Synthetic Data Generation
2:19: Data Configuration and Generation
3:06: Evaluating Synthetic Data Accuracy and Privacy
4:08: Rebalancing Datasets
5:54: Practical Applications for Data Science Teams