What is gradient descent, and how does it work?
- 1 Answers
- 186 Views
- I also Faced
- E-Mail Answers
Answer / Kumar Saurabh Pratap
Gradient Descent is an optimization algorithm used in machine learning to find the optimal parameters for a model by iteratively adjusting them based on the gradient (slope) of the cost function. It works by moving downhill along the negative gradient direction, which aims to minimize the cost function and improve the model's performance.
| Is This Answer Correct ? | 0 Yes | 0 No |
How can AI assist in early disease detection?
Explain the role of AI in loan approval processes.
How can AI be used to detect cyber threats?
Can you explain the concept of conversational AI and its applications in chatbots and virtual assistants?
Explain the role of GANs (Generative Adversarial Networks) in art creation.
How can you ensure transparency and accountability in an AI system?
What is the role of reinforcement learning in financial decision-making?
What are the differences between L1 and L2 regularization?
What is the role of AI in drug discovery?
What is the vanishing gradient problem in deep learning?
What are your career aspirations?
How does AI impact urban mobility and smart cities?
-
AI Algorithms (74) - AI Natural Language Processing (96)
- AI Knowledge Representation Reasoning (12)
- AI Robotics (183)
- AI Computer Vision (13)
- AI Neural Networks (66)
- AI Fuzzy Logic (31)
- AI Games (8)
- AI Languages (141)
- AI Tools (11)
- AI Machine Learning (659)
- Data Science (671)
- Data Mining (120)
- AI Deep Learning (111)
- Generative AI (153)
- AI Frameworks Libraries (197)
- AI Ethics Safety (100)
- AI Applications (427)
- AI General (197)
- AI AllOther (6)
