
Introducing the Data-Centric AI Community
A place to discuss data quality for data science.
Learn More
Are you intrigued by the possibilities of Data-Centric AI, and you want more?
Join like-minded experts, thought-leaders and peers at the Data-Centric Community!
Data-Centric AI is the process of building and testing AI systems by focusing on data-centric operations (i.e. cleaning, cleansing, pre-processing, balancing, augmentation) rather than model-centric operations (i.e. hyper-parameters selection, architectural changes).
Understanding the existing data is the first step. Profile your data in a few lines of code.
Explore your data with ydata-profiling!Synthetic data is artificially created data that keeps the original data properties, ensuring its business value while being privacy compliant.
Expand your data with ydata-synthetic!Isn't it one of your biggest pain points in data quality? The DCAI Community cultivates meaningful discussions around this and other topics!
A place to discuss data quality for data science.
Learn MoreA new paradigm for AI development — focused on data quality.
Learn MoreRead your data? Pause. Generate the Pandas Profiling report first.
Learn MoreGenerate synthetic sequential data with TimeGAN.
Learn MoreA tutorial on how you can combine ydata-synthetic with great expectations.
Learn MoreData labeling and data versioning provide a rock solid bedrock to build your machine learning models on now and in the future.
Learn More