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When should we use distributed computing?
When the data is huge and can not be processed using one machine
When the data is small and fast processing is required
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1 Introduction to Artificial Intelligence, Machine Learning and Deep Learning
2 How AI and ML can be used at your work, project or vertical?
3 Which of these are not sub-objectives of AI
4 What is the meaning of representing knowledge in the sub-objectives of AI?
5 What is rule-based programming?
6 AI is the final objective and software and hardware are tools to achieve AI
7 Deep Learning is one of the area in Machine Learning?
8 Deep Learning algorithm run faster on GPU
9 Deep learning algorithms cannot be run on CPU
10 What is machine learning?
11 In the example of automating the Mario game, how did the program collect the data?
12 Which of these are not Machine Learning applications
13 Deep learning takes inspiration from the biological neural networks of animal brains to achieve Intelligence
14 Do Deep Learning algorithms always give better accuracy than machine learning algorithms?
15 When should we use distributed computing?
16 For mathematical and graphics intensive workload, which type of processing works better
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