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 are Vanishing and Exploding Gradients?

1 Answers  

---

Please explain what is deep learning, and how does it contrast with other machine learning algorithms?

1 Answers  

---

What is the use of the activation function?

1 Answers  

---

What do you understand by deep autoencoders?

1 Answers  

---

What are the unsupervised learning algorithms in deep learning?

1 Answers  

---

What is Deep Learning?

1 Answers  

---

What is overfitting and underfitting?

1 Answers  

---

What are the differences between Machine Learning and Deep Learning?

1 Answers  

---

Are cuda cores important?

1 Answers  

---

How much gpu memory do I need?

1 Answers  

---

What is the difference between Epoch, Batch and Iteration in Deep Learning?

1 Answers  

---

What is Overfitting and Underfitting and how to combat them?

1 Answers  

---