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Algorithms | Coursera
Source: coursera.org
Article summary:
1. An algorithm is a set of clear steps to solve a problem in a particular class, and can be executed by both computers and humans.
2. Algorithms that computers work on deal with numbers, but we can represent other things as numbers so that computers can compute on them.
3. Designing an algorithm involves specifying exactly what you want the computer to do, dealing with error cases, and approaching the task in a disciplined fashion.
Article analysis:
The article provides a clear introduction to algorithms and their importance in solving problems. It highlights the fact that algorithms are not limited to computer programming but can also be executed by humans. The article also emphasizes the need for precise and unambiguous instructions when designing an algorithm.
However, the article has some potential biases and missing points of consideration. For example, it assumes that all algorithms deal with numbers, which is not entirely true. While many algorithms do involve numerical calculations, there are also algorithms that deal with text, images, and other types of data.
Additionally, the article focuses on the importance of planning and testing an algorithm before translating it into code. While this is certainly good advice, it does not address the fact that even well-planned algorithms can have unforeseen consequences or unintended outcomes. This is particularly relevant in fields such as artificial intelligence and machine learning where algorithms can have significant impacts on society.
Furthermore, the article does not explore counterarguments or alternative perspectives on algorithm design. For example, some experts argue that traditional algorithmic approaches may not be sufficient for solving complex problems in fields such as healthcare or climate science.
Overall, while the article provides a useful introduction to algorithms and their importance in problem-solving, it could benefit from a more nuanced discussion of their limitations and potential risks.