Data rarely comes in usable form. Data wrangling and exploratory data analysis are the difference between a good data science model and garbage in, garbage out.

In this section, we use the open data SFMTA Bikeway Network at San Francisco Data. The data include the network of bike routes, lanes, and paths around the city of San Francisco. Maintained by the ...

Coursera offers a variety of training options for the growing data professional. Explore top data science courses from Coursera now.

It’s time for the music industry to shift from endless data clean-up to a strategy of quality at the source, and transform data from a liability into a reliable asset. The following comes from Natalie ...

But, as a new survey of data scientists and machine learners shows, those expectations need adjusting, because the biggest challenge in these professions is something quite mundane: cleaning dirty ...

Fractured and incomplete datasets are a key barrier towards effectively training AI models for deployment in healthcare ...

American companies need new strategies for talent acquisition in data science and analytics.

While traditional data science practices have paved the way for critical insights and informed decision-making, AI has propelled the discipline into a new era of unprecedented speed, scale and ...

This data requires effective management and analysis to acquire factual results" including the "data cleansing, data mining, data preparation, and data analysis used in healthcare applications." ...