Using Synthetic Data for Machine Learning & AI in Python

Rewatch this training to discover what synthetic data is, how it protects privacy, and how it's being used to accelerate AI adoption in banking, healthcare, and many other industries.

Jul 12, 2023

Code along with us onCode Along

View Dataset

80% of AI projects fail, and more don't even start due to privacy constraints. This is where AI-generated synthetic data comes in. It's an anonymization technology seen as the key enabler for artificial intelligence.

Rewatch this training to discover what synthetic data is, how it protects privacy, and how it's being used to accelerate AI adoption in banking, healthcare, and many other industries. You will create a highly representative synthetic dataset yourself, learn how to assess its quality and use it for privacy-preserving machine learning. And as a bonus exercise, we'll look into smart imputation with synthetic data to save you time on data pre-processing!

Key Takeaways:

Learn when synthetic data can be helpful for protecting privacy.
Learn how to create synthetic datasets.
Learn how to assess the quality of synthetic datasets.

Additional Resources

Code along with Alexandra on DataLab

Generate synthetic data using MOSTLY AI - Use the ‘AI/ML training’ set

Topics

Data Science

DataLab

Python

Artificial Intelligence (AI)

blog

What is Synthetic Data?

Synthetic data is artificially generated data that mimics the characteristics of real-world data without containing any actual information.

Abid Ali Awan

6 min

tutorial

Creating Synthetic Data with Python Faker Tutorial

Generating synthetic data using Python Faker to supplement real-world data for application testing and data privacy.

Abid Ali Awan

13 min

tutorial

Preprocessing in Data Science (Part 3): Scaling Synthesized Data

You can preprocess the heck out of your data but the proof is in the pudding: how well does your model then perform?

Hugo Bowne-Anderson

10 min

code-along

Machine Learning in Production with Python

Michelle Conway, Lead Data Scientist at Lloyds Banking Group, will walk you through a simple machine learning example on banking data, including feature engineering, training a model, making predictions, and assessing model performance.

Michelle Conway

code-along

Getting Started with Machine Learning in Python

Learn the fundamentals of supervised learning by using scikit-learn.

George Boorman

code-along

Using AI to Enhance Product Pages with LangChain and Python

In this webinar, you'll learn how to use generative AI tools, including LangChain, to make better retail product pages.

Jikku Jose

See More See More