Two of the most talked-about subfields of artificial intelligence (AI) are machine learning and deep learning. They are not the same thing, even though they are frequently used interchangeably. Businesses and organizations looking to implement AI-based solutions need to know the difference between the two.
Cloud security refers to the measures taken to protect data and applications hosted on cloud computing platforms. It offers several benefits such as scalability, flexibility, cost-effectiveness, and accessibility. However, it also has limitations that need to be considered.
In today’s digital age, the need for strong passwords and effective password management has never been greater. With increasing numbers of online accounts, it is important to take the necessary steps to protect personal and sensitive information from the risk of cyber-attacks.
Usually, knowing what values you should use for the hyperparameters of a specific algorithm on a given dataset is challenging. That’s why you need to explore various strategies to tune hyperparameter values. With hyperparameter tuning, you can determine the right mix of hyperparameters that would maximize the performance of your model.
The domains of finance and health care don’t have much in common except for one thing - the involvement of data scientists and machine learning experts, who are changing the way both these domains work. From helping them collect, organize, and process a massive volume of data and making sense of it to letting them make efficient and faster data-driven decisions, a lot is happening to disrupt both these domains. Let’s consider some examples from both the finance and healthcare sectors to understand how the application of data science is helping them.
It’s normal today to talk about the massive computing power of supercomputers, the domain of data science that facilitates data availability and analysis, among others, and AI that can mimic mental actions similar to humans. But the road to the modern world’s AI, big data, and deep learning has been a long one. Let’s take a tour down the historical avenues to find how AI evolved into what it is today.