Terminology for interview preparation

 

The complete Machine Learning Terminology for interview preparation✍️‍💻

In this article, I will present concise definitions for key terms in the field of machine learning, ordered to align with the typical progression of the machine learning process. These definitions have been derived from ChatGPT and have been carefully refined to maximize clarity making them easily comprehensible to readers. I have covered almost every term involved in machine learning if I missed any terms kindly comment in chat window so myself and other readers can be able to know and get aware.

✅Machine Learning- A subset of artificial intelligence where computer systems learn from data to improve performance on a specific task.

✅Artificial Intelligence- The simulation of human intelligence processes by machines, including learning, reasoning, and problem-solving.

✅Data- Raw information or facts collected and stored for analysis.

✅Feature- A distinct property or characteristic in the dataset used to make predictions in machine learning.

✅Label- The outcome or target variable that machine learning models aim to predict.

✅Supervised Learning- A machine learning approach where models learn from labeled data with known outcomes.

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