Ep. 11: Clearing the confusion: AI vs Machine Learning vs Deep Learning

What this episode covers

On today’s episode, Asim Razzaq elaborates on the misconceptions between artificial intelligence, machine learning, deep learning, and data science. While many might not be able to see the difference in the 4 fields, experts are still advised to know how each of these work, and the outcomes and process are definitely not the same. [00:57] The Misconceptions of AI, ML, DL, and DS [01:57] How They Are Related [02:01] Artificial Intelligence [04:06] Machine Learning [06:50] Deep Learning [07:48] Data Science [08:09] In Application [09:27] Summary Need-to-Know In an age where AI and ML are progressively developing, engineers are advised to recognize the difference between the four categories of artificial intelligence, machine learning, deep learning, and data science. It is crucial and important for experts in the field that despite being an expert in a certain sector, you will either be indirectly or directly exposed to one or all of these elements down the line. Related But Different Functions All four categories are related, but each field has a specific function that defines them for that particular category. While AI is the general domain, ML, DL, and DS bring a different type of tool into the spectrum. It is important to know what sets these domains apart from one another by looking at the methods and processes on how they run, as well as the ultimate contribution to the solution.

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