Answer / Sajal Sharma

Bagging (Bootstrap Aggregating) is an ensemble method used in machine learning that creates multiple subsets of the training data through random sampling with replacement, trains a decision tree on each subset, and averages their results to reduce variance. Boosting, on the other hand, is another ensemble method where weak learners are combined to create a strong learner by iteratively training models that focus on misclassified instances in the previous round.

What do you understand by deep learning?

1 Answers  

---

What is the use of the activation function?

1 Answers  

---

What do you mean by dropout?

1 Answers  

---

What are the Softmax and ReLU functions?

1 Answers  

---

Can radeon run cuda?

1 Answers  

---

What are the applications of deep learning?

1 Answers  

---

Differentiate supervised and unsupervised deep learning procedures.

1 Answers  

---

Which gpu is best for deep learning?

1 Answers  

---

What are the issues faced while training in recurrent networks?

1 Answers  

---

What was deep learning?

1 Answers  

---

Are cuda cores important?

1 Answers  

---

Is gtx 1060 good for deep learning?

1 Answers  

---