Answer / Manish Kumar Tripathi

"Data cleansing, or data cleaning, is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in datasets. It's crucial for ensuring that the data used for analysis is reliable and accurate. Poor quality data can lead to misleading results, wrong conclusions, and poor decision-making. Data cleansing helps maintain data integrity, improves data consistency, enhances data security, and reduces operational costs."n

How would you explain Machine Learning to a school-going kid?

1 Answers  

---

Differentiate supervised and unsupervised machine learning.

1 Answers  

---

Explain how can we use your machine learning skills to generate revenue?

1 Answers  

---

What’s the difference between a generative and discriminative model?

1 Answers  

---

Tell me what is the most frequent metric to assess model accuracy for classification problems?

1 Answers  

---

Tell us how do deductive and inductive machine learning differ?

1 Answers  

---

Can you name some popular machine learning algorithms?

1 Answers  

---

What is collaborative filtering in machine learning?

1 Answers  

---

What is the sigmoid function in machine learning?

1 Answers  

---

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

1 Answers  

---

What is the “curse of dimensionality?

1 Answers  

---

Which language is best for deep learning?

1 Answers  

---