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Computer Vision (1)
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Natural Language Processing

Q. Adapting Large Language Models to your app: a practical guide
Q. Explain Perplexity
Q. What are some of the approaches for decoding the next word in LLMs?
Q. Explain BLEU (Bilingual Evaluation Understudy)
Q. What are Embeddings?
Q. What are Language Models? Discuss the evolution of Language Models over time
Q. What is Natural Language Processing (NLP) ? List the different types of NLP tasks
Q. What are some of the most common practical, real world applications of NLP?
Q. What is topic modeling? Discuss key algorithms, working, applications, and the pros and cons
Q. What is Bag-of-Words Model? Explain using an example
Q. What are some use cases of Bag of Words model?
Q. What are the advantages and disadvantages of Bag-of-Words model?
Q. How is topic modeling used in text summarization?
Q. What is an N-gram Language model? Explain its working in detail
Q. What is Term Frequency (TF)?
Q. What is IDF? What do we need IDF?
Q. What is tokenization?
Q. What is Lemmatization?
Q. What are the Advantages/Disadvantages of a n-gram model
Q. In what cases (and why) does using Binary Occurrence instead of TF-IDF makes more sense?
Q. What is Vector Normalization? How is that useful?
Q. What is the problem with using a generic list of stop words?
Q. How to identify Stop Words?
Q. What happens to new words that appear in Test dataset but are not present in Training Data?
Q. What is Laplace Smoothing? What is Additive Smoothing? Why do we need smoothing in IDF?
Q. What is a Vector Space Model?
Q. What is meant by Corpus and Vocabulary in Natural Language Processing?

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Explore Questions by Topics

Computer Vision (1)
Generative AI (2)
Machine Learning Basics (18)
Deep Learning (52)
- DL Basics (16)
- DL Architectures (17)
  - Feedforward Network / MLP (2)
  - Sequence models (6)
  - Transformers (9)
- DL Training and Optimization (17)
Natural Language Processing (27)
- NLP Data Preparation (18)
Supervised Learning (115)
- Regression (41)
  - Linear Regression (26)
  - Generalized Linear Models (9)
  - Regularization (6)
- Classification (70)
  - Logistic Regression (10)
  - Support Vector Machine (9)
  - Ensemble Learning (24)
  - Other Classification Models (9)
  - Classification Evaluations (9)
Unsupervised Learning (55)
- Clustering (37)
  - Distance Measures (9)
  - K-Means Clustering (9)
  - Hierarchical Clustering (3)
  - Gaussian Mixture Models (5)
  - Clustering Evaluations (6)
- Dimensionality Reduction (9)
Statistics (34)
Data Preparation (35)
- Feature Engineering (30)
- Sampling Techniques (5)

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Other Questions in Natural Language Processing

How does hinge loss differ from logistic loss?
Describe briefly the training process of a Neural Network model
How does pruning a tree work?
Explain Perplexity
What are some pros and cons of Discriminant Analysis?
What is the difference between a Probability Mass Function (PMF), Probability Density Function (PDF), and Cumulative Distribution Function (CDF)?

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