Researchers and data scientists are employing synthetic data to create new products, improve machine learning model performance, substitute sensitive data, and save money on data acquisition expenditures. In this article, we will see how to generate synthetic tabular data using GANs. What is CTGAN? ...

Information that has been created intentionally rather than as a result of actual occurrences is known as synthetic data. Synthetic data is generated algorithmically and is used to train machine learning models, verify mathematical models, and act as a stand-in for test datasets of production or ope...

Introduction Data scientists all across the world are hungry for it. The ambition to train and deploy cutting-edge machine learning algorithms such as neural networks raise the bar for additional data. This rapidly becomes an issue when gathering fresh data is time-consuming, expensive, or just impo...

In this article, we will look at the Synthetic Data Vault – A Framework to generate Synthetic Data. Introduction The Synthetic Data Vault (SDV) is a library ecosystem that allows users to rapidly study single-table, multi-table, and timeseries datasets in order to produce new Synthetic Data with t...

Using actual production data in a test environment was once a no-brainer for most engineers. However, in the aftermath of privacy legislation such as GDPR, it is simply no longer an option. You can’t take those kinds of risks with actual people’s data – and if you do, you’ll ...

Introduction In 2020, artificial intelligence is all the rage, but many aspiring engineers are bumping across a stumbling block: training data. Most artificial intelligence/machine learning applications require a big, vetted dataset. Obtaining that data is frequently difficult. You must not only col...

One of today’s most precious resources is data. However, due to the cost, sensitivity, and processing time, obtaining real data is not always a possibility. However, synthetic data might be a useful option for training machine learning models. In this post, we will define synthetic data in mac...

Data is one of today’s most valuable resources. However, because actual data is expensive, sensitive, and time-consuming to collect, it is not always a choice. When training machine learning models, however, utilizing synthetic data may be a valuable replacement. In this post, we will define s...

Data is the foundation of every data project; data analysis, machine learning model training, and even a simple dashboard all require data. As a result, gathering the data required for your project is critical. However, it is not always the case that the data you seek exists or is publicly accessibl...

Synthetic data is annotated information generated by computer simulations or algorithms as a substitute for real-world data. To put it another way, synthetic data is generated in digital environments rather than being gathered or measured in the actual world. Although it is artificial, synthetic dat...