Answer / Kavita

Methods of reducing dimensionality in machine learning include Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), t-SNE, and autoencoders. These techniques aim to find lower-dimensional representations of the original data while preserving essential information.

What is the benefit of naïve bayes mcq?

1 Answers  

---

What do you mean by regression in machine learning?

1 Answers  

---

How machine learning is deployed in real world scenarios?

1 Answers  

---

Explain true positive, true negative, false positive, and false negative in confusion matrix with an example.

1 Answers  

---

What do you mean by ensemble learning?

1 Answers  

---

What is ‘tuning’ in ML?

1 Answers  

---

How is ML different from artificial intelligence?

1 Answers  

---

Is naive bayes supervised learning?

1 Answers  

---

Explain how do you ensure you're not overfitting with a model?

1 Answers  

---

Which is better for image classification? Supervised or unsupervised classification? Justify.

1 Answers  

---

How can you ensure that you are not overfitting with a particular model?

1 Answers  

---

What are the different methods for Sequential Supervised Learning?

1 Answers  

---