Answer / Santosh Kumar Bhart

Machine Learning covers a wide range of topics, including Supervised Learning (learning from labeled data), Unsupervised Learning (learning from unlabeled data), Reinforcement Learning (learning through interaction with an environment), Deep Learning (using artificial neural networks with many layers to learn hierarchical representations), and Transfer Learning (reusing trained models on different but related tasks).

What is Bayes theorem in artificial intelligence?

1 Answers  

---

What is the Applying the model in Machine Learning?

1 Answers  

---

Which language is better for machine learning?

1 Answers  

---

Why naive bayes is called naive?

1 Answers  

---

What was bayes’ theorem? How was it useful in a machine learning context?

1 Answers  

---

What is the baseline for machine learning?

1 Answers  

---

Pick an algorithm and write a Pseudocode for the same?

1 Answers  

---

What is the difference between heuristic for rule learning and heuristics for decision

1 Answers  

---

How does deductive and inductive machine learning differ?

1 Answers  

---

What are the recommended systems?

1 Answers  

---

Name a few libraries in Python used for Data Analysis and Scientific Computations?

1 Answers  

---

Explain why Navie Bayes is so Naive?

1 Answers  

---