Explain the concept of embeddings and their use in NLP.

51

---

What are some challenges in building high-quality generative models?

68

---

Explain the concept of Q-learning.

57

---

Explain how you would debug a machine learning model that is not performing well.

63

---

What are the challenges of implementing AI on edge devices?

63

---

How can AI personalize the learning experience in education?

58

---

Explain the concept of active learning and when it's useful.

74

---

Describe how you would build a chatbot.

60

---

What are some common evaluation metrics for classification and regression problems?

62

---

How can AI be used to address climate change?

52

---

Describe regularization techniques and why they're used.

69

---

What are the limitations when applying AI in climate modeling?

60

---

What are some emerging trends in multimodal AI?

62

---

How do you handle missing or dirty data?

56

---

How do you deal with performance degradation of a model over time (model drift)?

65

---