A problem from econometrics illustrates the difference between artificial and human intelligence. Understanding tacit knowledge and the limits of AI is crucial to deploying it effectively and fairly.
By leveraging natural language processing, augmented analytics could revolutionize the way data science teams — and non-specialist business users — get the information their firms need.
As a data scientist, you may be able to get away without using linear algebra — but not for long. Here’s how linear algebra can improve your machine learning, computer vision and natural language processing.
In order to use data effectively for any kind of analysis, data scientists must be able to clean and prepare it first. Fortunately, Python makes doing so easy.