People have always been fascinated by the idea of giving human-like characteristics to inanimate objects. A major component of this over the last century has been the focus on creating “thinking machines.” Advancements in programming and processing have introduced concepts such as machine learning and deep learning into our vocabularies. However, although these terms may be used interchangeably by some, they are different concepts. For starters, artificial intelligence refers to anything that can perform an intellectual task usually performed by a human. The most basic form of this is “if/then” programming. If a computer encounters a specific parameter in its program, the program tells it what to do next. Machine learning, on the other hand, means systems can learn to perform tasks by themselves without human intervention through continued exposure to data. Some examples of this principle in action include weather forecasting and antivirus software. The more information these are exposed to, the more accurate their predictions and conclusions will be. As these innovations continue to evolve, so too will the utility they provide. To learn more about these concepts and the ways in which they’re contributing to our lives, be sure to read on to the resource paired alongside this post.
Python Programming & Its Importance In Machine Learning provided by Accelebrate, a company offering courses in Python Data Science training