Data can often feel overwhelming—rows upon rows of numbers, scattered information, and endless spreadsheets that seem to blur together. If you’ve ever stared at a dataset wondering how to make sense ...

Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to show how to programmatically normalize numeric data for use in a machine learning system such as a deep neural ...

As artificial intelligence (AI) speeds up and simplifies technical tasks, the ability to think creatively and communicate visually will be the competitive edge that sets the next generation of data ...

Visualizing time series data is often the first step in observing trends that can guide time series modeling and analysis. As time series data analysis becomes more essential in applications across ...

The t-SNE ("t-distributed Stochastic Neighbor Embedding") technique is a method for visualizing high-dimensional data. The basic t-SNE technique is very specific: It converts data with three or more ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

See our top data 8 visualization tools, including Tableau, Power BI and Google Looker, learn why we selected each and understand how to determine the best visualization tool. Data visualization tools ...

Quantile normalization is an important normalization technique commonly used in high-dimensional data analysis. However, it is susceptible to class-effect proportion effects (the proportion of ...

Normalization is essential to get rid of biases in microarray data for their accurate analysis. Existing normalization methods for microarray gene expression data commonly assume a similar global ...