Remove Computer Science Remove Decision Trees Remove Natural Language Processing Remove Predictive Analytics
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2024 Tech breakdown: Understanding Data Science vs ML vs AI

Pickl AI

AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. Skills Proficiency in programming languages (Python, R), statistical analysis, and domain expertise are crucial.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

Because the datasets are unstructured, though, it can be complicated and time-consuming to interpret the data for decision-making. That’s where data science comes in. The term data science was first used in the 1960s when it was interchangeable with the phrase “computer science.”

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Five machine learning types to know

IBM Journey to AI blog

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g.,