🚀 MOSTLY AI releases World’s First Industry-Grade Open-Source Toolkit for Synthetic Data

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Videos

Videos

Learn how MOSTLY AI is utilizing synthetic data and privacy tech to change how modern businesses approach their data.

October 30, 2023

Mastering Multi-Table Data Synthesization with MOSTLY AI: A Comprehensive Tutorial

Generating synthetic data with multi-tables should not be a daunting task. Using this comprehensive tutorial and MOSTLY A's free synthetic data platform, anyone can master multi-table synthetic data generation. We will guide you through each step, ensuring you have a clear understanding of how to handle and synthesize relational data structures effectively. Dive deep into […]

October 23, 2023

Democratize your data with MOSTLY AI

🔒 What if we lived in a society where everyone could harness the power of data without compromising privacy? 📊 Imagine a world where data-driven decisions were accessible to all, regardless of their technical background. In this thought-provoking video, Tobias Hann, CEO of MOSTLY AI, the pioneering synthetic data company, explore the potential of synthetic […]

October 18, 2023

Data visualization on MOSTLY AI's synthetic data generation platform

MOSTLY AI's synthetic data platform now offers an incredible schema visualization feature for multi-tables. The Relationship Diagram allows users to effortlessly verify the relationship configurations and to synthesize data with referential integrity. Check out the video to see the Relationship Diagram in action! Better yet, try it yourself for free on the world's most accurate […]

October 17, 2023

AI-generated Synthetic Data vs. Mock Data

Have you ever wondered what the difference is between synthetic data and mock data? In this video, we'll provide you with an objective analysis of the quantitative differences between these two data generation methods. This knowledge can empower you to make informed decisions when working with diverse data types in your data science and analytics […]

October 16, 2023

Synthetic Text Generation Tutorial

Welcome to this comprehensive tutorial on synthetic text generation using MOSTLY AI's synthetic data generation platform. In this tutorial, we'll guide you through the process of creating high-quality synthetic text data and ensuring its statistical representativeness. Here is what we cover: 1. Introduction to Synthetic Text Generation (0:00) 2. The Power of Synthetic Text Data […]

October 12, 2023

Synthetic Data Quality Evaluation Tutorial: Train-Synthetic-Test-Real Using AutoML on Databricks

This tutorial demonstrates the Train-Synthetic-Test-Real (TSTR) evaluation method to assess the quality of synthetic data. This approach ensures that Machine Learning models trained on synthetic data perform effectively, providing a reliable measure of the data’s utility for downstream ML tasks. Here is what you'll learn: [00:00 – 00:06] What is the TSTR Evaluation Method [00:06 […]

October 12, 2023

Fake or real? How to use a data discriminator for evaluating synthetic data quality

Dive deep into this tutorial on how to construct a machine learning model that effectively differentiates between fake and real data records. Whether you're trying to assess the quality of synthetic data or discern hybrid datasets, this guide will prove invaluable. Here is what you'll learn: 00:00-00:02 - Fake vs Real Data Discriminator 00:05-00:20 - […]

September 21, 2023

Explainable AI with Synthetic Data Tutorial

📚 In this tutorial, we'll show you how to make AI more explainable using synthetic data. Synthetic data helps you to alleviate privacy concerns and make your machine learning models more transparent and accountable. Chapters: 00:00:00 | Introduction 00:00:06 | Overview of Explainable AI with Synthetic Data 00:00:36 | Training the Model on Real Data […]

September 21, 2023

Conditional synthetic data generation tutorial

👋 Welcome to this comprehensive tutorial on Conditional Synthetic Data Generation! In this tutorial, you'll learn how to exercise more control over the synthetic data you generate. By the end, you'll understand how to apply conditional generation in two different scenarios: equalizing gender income distribution in the UCI Adult Income dataset and maintaining the geographic […]

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