Assuming you have a csv file with a few rows of data and you want to generate 1000s of additional rows with similar data, you can use Python’s Pandas library…
The Faker library is used to generate fake data, such as names, addresses, phone numbers, dates, and other types of data. The available functions in the Faker library depend on…
The Faker library in Python supports generating fake data in a wide range of languages. By default, the library generates data in English, but you can specify a different language…
Here’s an example of how you can generate a fake text column with some data augmentation technique using the Faker library in Python: In this example, we read the input…
Here’s an example of how you can use a pre-trained language model to generate fake text that matches the words in the sample text column: In this example, we load…
Every ML project is unique and has different requirements. However, here is a recommended architecture using AWS technologies that involves end to end life cycle of a ML Project: Overall,…
Amazon Athena is a serverless query service that allows you to easily analyze and query data stored in Amazon S3 using standard SQL. With Athena, you can quickly run ad-hoc…
There are many case studies of machine learning (ML) projects where data augmentation played a key role in the success of the project. Here are a few examples: These are…
Generative AI and data augmentation share some similarities, but they are not the same thing. Data augmentation is a technique used to artificially increase the size of a dataset by…
Generative AI can be used to increase the size of a training dataset by generating synthetic data that is similar to the real data. This approach is known as data…