Interested to Buy Any Domain ? << Click Here >> for more details...
What was bayes’ theorem? How was it useful in a machine learning context?
- 1 Answers
- 188 Views
- I also Faced
- E-Mail Answers
Answer / Phool Chand
Bayes' theorem is a fundamental principle in probability theory that describes the conditional probability of an event A given another event B. In machine learning, it is used to calculate the posterior probability of a hypothesis given observed evidence, which is essential for Bayesian classification and regression tasks.
| Is This Answer Correct ? | 0 Yes | 0 No |
What is Seq2Seq Tensorflow?
What is bias and variance in a Machine Learning model?
How do you think google is training data for self-driving cars?
Explain how do you handle missing or corrupted data in a dataset?
How do you ensure you're not overfitting with a model?
How is ML different from artificial intelligence?
How will you design an email spam filter?
What is symbolic reasoning?
What’s your favorite algorithm, and can you explain it to me in less than a minute?
What are the three stages of building the hypotheses or model in machine learning?
What are the most important machine learning techniques?
What's the “kernel trick” and how is it useful?
-
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)
