Beginners should undertake data science projects as they provide practical experience and help in the application of theoretical concepts learned in courses, building a portfolio and enhancing skills.

Did you know that over 80% of AI projects fail? That's twice the failure rate of regular IT projects. A Gartner survey found that only 48% of AI projects make it to production, and it typically takes ...

Nine data-driven research projects have won funding from Princeton University’s Schmidt DataX Fund, which aims to spread and deepen the use of artificial intelligence and machine learning across ...

Shivanku Misra is an AI expert, currently serving as Vice President overseeing enterprise advanced analytics and AI initiatives at McKesson. In the rapidly evolving field of data science, the success ...

“If your competitors are applying AI, and they’re finding insight that allow them to accelerate, they’re going to peel away really, really quickly,” Deborah Leff, CTO for data science and AI at IBM, ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your toolkit. Python’s rich ecosystem of data science tools is a big draw for ...

Company to add predictive intelligence on planned infrastructure investments for verticals such as broadband, waste management, power and electricity, and renewable energy TORONTO--(BUSINESS ...

In the rapidly evolving field of Data Science, technical skills such as programming, statistics, and machine learning are often emphasised as the foundation for success. However, while these are ...