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What are the three stages of building the hypotheses or model in machine learning?
Can you explain the concept of generative adversarial networks (GANs) and their implications for AI?
Explain the difference between data modeling and database design?
Is tensorflow open source?
What is an api? What are apis used for?
How can you find overfitting in tensforflow ? How can you avoid it ?
What is a Large Language Model (LLM), and how does it work?
How many layers in CNN ? How they mean ?
Which of the data augmentation technique would you prefer for an object recognition problem?
This list covers a wide spectrum of topics, ensuring readiness for interviews in Generative AI roles.
Which were built in such a way that humans had to supply the inputs and interpret the outputs? a) Agents b) AI system c) Sensor d) Actuators
What do you understand by the confusion matrix?
How would you handle imbalanced datasets?
Which kind of agent architecture should an agent an use? a) Relaxed b) Logic c) Relational d) All of the mentioned
What are the differences between knowledge representation methods like Semantic Networks and Ontologies?
