Answer / Nirmal Kishore Pandey

Data normalization, also known as feature normalization, is a preprocessing technique used to standardize the range of continuous features within a dataset. It aims to scale each feature to have a mean of 0 and a standard deviation of 1. Normalization can help improve model convergence, prevent dominant features from influencing the results, and make the learning process more stable.

Explain the difference between machine learning and regression?

1 Answers  

---

Why Accuracy is important in machine learning?

1 Answers  

---

What are the most common types of machine learning task?

1 Answers  

---

What is the difference between an array and Linked list in Machine learning?

1 Answers  

---

What is data normalization in ml?

1 Answers  

---

What evaluation approaches would you work to gauge the effectiveness of a machine learning model?

1 Answers  

---

What's the f1 score? How would you use it?

1 Answers  

---

What is the Model testing in Machine Learning?

1 Answers  

---

What is an imbalanced dataset? Can you list some ways to deal with it?

1 Answers  

---

What is A/B Testing?

1 Answers  

---

What is the difference between artificial intelligence and machine learning?

1 Answers  

---

Explain the difference between bayesian and frequentist?

1 Answers  

---