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    50 Solved MCQs on Generative AI

    50 Solved MCQs on Edge Computing 1. What is Edge Computing? A) Centralized computing B) Computing at the edge of the network C) Computing in the cloud D) Only mobile computing   Answer: B Explanation:  Edge computing processes data near the data source (like sensors/devices), reducing the need to send it to centralized data centers. 2. What is the main benefit of edge computing? A) Higher latency B) Slower processing C) Reduced latency D) Increased bandwidth usage   Answer: C Explanation:  By processing data close to where it’s generated, edge computing reduces latency. 3. Which of the following is an example of edge computing? A) A central cloud server storing data B) A smartphone analyzing video in real-time C) A data center running AI models D) A storage backup system   Answer: B Explanation:  A smartphone analyzing video locally without sending it to the cloud is an edge computing application. 4. Edge devices are often: A) Large server...

Machine Learning MCQs - Basics & Supervised Learning Machine Learning MCQs machine Learning mcqs Basics & Supervised Learning (1-100) 1. What is the main goal of supervised learning? A. To group data without labels B. To discover hidden patterns C. To learn a mapping from inputs to known outputs D. To minimize entropy Answer: C Supervised learning uses labeled data to train models to predict outcomes based on input. 2. Which of the following is a supervised learning algorithm? A. K-means B. Linear Regression C. PCA D. DBSCAN Answer: B Linear Regression is a supervised learning algorithm that models the relationship between inputs and outputs. 3. What is the difference between classification and regression? A. Classification predicts continuous output, regression predicts categories B. Classification predicts categories, regression predicts continuous out...