Answer / Neelambuj Kumar Shrivastava

Overfitting occurs when a machine learning model learns the training data too well, to the point where it performs poorly on new, unseen data. The model may capture noise or irrelevant patterns in the training data that are not representative of the actual problem. Underfitting, on the other hand, happens when the model is too simple and cannot capture the underlying relationships in the data, resulting in poor performance both during training and testing.

What is data normalization and why do we need it?

1 Answers  

---

Is 8gb ram enough?

1 Answers  

---

What is Dropout and Batch Normalization?

1 Answers  

---

What is encoder in deep learning?

1 Answers  

---

How much gpu memory do I need?

1 Answers  

---

What are the issues faced while training in recurrent networks?

1 Answers  

---

What is a gpu used for?

1 Answers  

---

Tell me how does deep learning contrast with other machine learning algorithms?

1 Answers  

---

What is the softmax function?

1 Answers  

---

Is rtx 2060 good for deep learning?

1 Answers  

---

What are the applications of deep learning?

1 Answers  

---

What is overfitting and underfitting?

1 Answers  

---