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complex time series

Synthetic Multivariate Time Series Data

Generating synthetic versions of complex time series data As we saw in our previous post, YData Fabric’s time series synthesizer works well for univariate, single-entity datasets, regardless of how complex the processes generating those...

Unvariate Graphic

Simple Synthetic Time Series Data

Generating synthetic versions of simple time series data Time series data is all around us, from health metrics to transaction logs. The increasing proliferation of IoT devices and sensors means that more and more time series data is...

Data-Centric AI from the perspective of a statistician

Data-Centric AI — A Statistician’s View

How data improves models by lessening uncertainty It’s not every day that I read an academic paper that does a perfect job of balancing philosophical rigor and technical depth. I love deeply technical and applied ML research that drives...

Generative AI Model for Time-Series Synthetic Data Generation

The best Generative AI Model for Time-Series Synthetic Data Generation

Exploring TimeGAN and YData Fabric for Synthetic Data Generation of Temporal Patterns In order to accelerate AI development and guarantee the best business practices and results, organizations rapidly need to become more data-centric....

The importance of Data Catalogs for Machine Learning initiatives - Fabric the data catalog for data science

Unlocking the Power of a Data Catalog for Your Business

The importance of data quality & profiling for the success of Machine Learning In today's world, businesses around the globe are generating a vast amount of data. To be able to adopt a data-driven initiative, organizations must manage data...

High-quality data is a concern for all the elements of the modern data teams: from data engineers to data scientists.

The different dimensions for high-quality data in AI

Cover Photo by John Schnobrich on Unsplash Data Engineering vs Machine Learning the differences and overlaps Data quality is critical to both Data Engineering and Data Science, after all poor quality data can be costly quite costly for a...

Explaining Imbalanced Data, DCAI

What is imbalanced data in Machine Learning?

Data quality plays a crucial role in the success of machine learning projects. In the realm of artificial intelligence, where algorithms learn from data to make predictions and decisions, the quality of the input data directly impacts the...

Top 5 Python Packages Python Synthetic Data

The Top 5 Python Packages to Generate Realistic Synthetic Data

Cover Photo by Xiang Gao on Unsplash Get started with Synthetic Data Generation with these Open Source Libraries Following the extraordinary advances of Generative AI models, Synthetic Data is becoming the standard for Machine Learning...

Time-series structure and how it impacts data quality profiling and synthetic data generation

Understanding the Structure of Time-Series Datasets

Unveiling the inner workings of how sequential data works and how Fabric can to smooth your journey in a time-series Machine Learning project Time-series data refers to a type of data that is collected and recorded over time and can be...

ydata-synthetic the open-source for synthetic data generation

Synthetic data generation with Gaussian Mixture Models

Photo by Roman Synkevych on Unsplash A probabilistic approach to fast synthetic data generation with ydata-synthetic To find synthetic data generation within the same sentence as Gaussian Mixture Models (GMMs) sounds odd, but it makes a...

Synthetic Data for Aligning ML Models to Business Value

Synthetic Data for Aligning ML Models to Business Value

I improved a model to save a hypothetical auto insurance company almost $200 per claim! One of the biggest mistakes that junior data scientists make is focusing too much on model performance while remaining naive about the model’s impact...

Synthetic Data

10 Most Asked Questions on ydata-synthetic

1. What is the ydata-synthetic and what does it do? ydata-synthetic is an open-source Python package developed by YData’s team that allows users to experiment with several generative models for synthetic data generation. The main goal of...

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