Digging beyond the standard data profiling Pandas Profiling was always my goto-secret tool to understand the data and uncover meaningful insights, in a few minutes, under a few lines of code. Whenever I was given a new dataset, I would...
Data-centric AI and the reshape of the tooling space The end-to-end development of Data Science solutions can be broadly described as the process of analysis, planning, development and operationalization of a business problem that can be...
A guide to go a step beyond with your data Lately, there has been a lot of discussion about data quality and its impacts on model performance. Mainly due to this presentation which highlighted this topic — model-centric vs data-centric,...
A place to discuss data quality for data science According to Alation’s State of Data Culture Report, 87% of employees attribute poor data quality to why most organizations fail to adopt AI meaningfully. Based on a 2020 study by McKinsey,...
A tutorial on how you can combine ydata-synthetic with Great Expectations With the rapid evolution of machine learning algorithms and coding frameworks, the lack of high-quality data is the real bottleneck in the AI industry. Transform...
Introducing YData Quality: An open-source package for comprehensive Data Quality. Flag all your data quality issues by priority in a few lines of code “Everyone wants to do the model work, not the data work” — Google Research According to...
A vibrant community pioneering an essential to the data science toolkit According to a 2017 Harvard Business Review study, only 3% of companies’ data meets basic quality standards. Based on a 2020 YData study, the biggest problem faced by...
According to the 2021 enterprise trends in machine learning report by Algorithmia, 83% of all organizations have increased their AI/ML budgets year-on-year, and the average number of data scientists employed has grown by 76% over the same...
A new paradigm for AI development — focused on data quality In my last blog post I’ve covered the rise of DataPrepOps and the importance of data preparation to achieve optimized results from Machine Learning based solutions. The stakes of...
Modern data development tools and how data quality impacts ML results ML is all around us! From healthcare to education, it is being applied in many domains that affect our daily activities and it’s able to deliver many benefits. Data...
An odyssey on improving data quality with synthetic data and model delivery with MLOps Machine Learning and AI are two concepts that definitely have changed our way of thinking in the last decade, and will probably change even more in the...
Generate synthetic sequential data with TimeGAN Time-series or sequential data can be defined as any data that has time dependency. Cool, huh, but where can I find sequential data? Well, a bit everywhere, from credit card transactions, my...
