Answer / Anand Tiwari

Machine Learning and Data Mining are two distinct but related fields within the broader realm of artificial intelligence (AI).nData Mining is the process of discovering patterns in large datasets using statistical and mathematical techniques. It focuses on finding hidden relationships, anomalies, trends, and sequences in the data without needing to follow an explicit algorithm.nMachine Learning, on the other hand, involves training algorithms to make predictions or decisions based on past data. The goal is for these algorithms to learn patterns from the input data and use that knowledge to perform tasks such as classification, regression, or clustering.nIn short, Data Mining is more focused on discovering patterns and relationships within datasets while Machine Learning emphasizes the building of models capable of learning from and making predictions based on those patterns.

What is svm in machine learning? What are the classification methods that svm can handle?

1 Answers  

---

How to handle missing data in a dataset in Machine Learning?

1 Answers  

---

What is the standard approach to supervised learning?

1 Answers  

---

What is root cause analysis?

1 Answers  

---

Explain the difference between type I and type ii error?

1 Answers  

---

Why do ensembles typically have higher scores than individual models?

1 Answers  

---

What is ‘Training set’ and ‘Test set’?

1 Answers  

---

How can we use your machine learning skills to generate revenue?

1 Answers  

---

What is the difference between Gini Impurity and Entropy in a Decision Tree?

1 Answers  

---

Explain how do you think google is training data for self-driving cars?

1 Answers  

---

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

1 Answers  

---

What is the method to avoid overfitting?

1 Answers  

---