Interview Questions and Answers

Use Twitter API to extract tweets, perform text analysis to identify top discussed topics.

• Access Twitter API to retrieve tweets

• Perform text analysis using NLP techniques like TF-IDF or LDA

• Identify keywords or hashtags with highest frequency to determine top discussed topics

I use models like LSTM, BERT, and Transformer for sentiment analysis and summarization.

• LSTM (Long Short-Term Memory) for sequence prediction tasks like sentiment analysis

• BERT (Bidirectional Encoder Representations from Transformers) for contextual word embeddings

• Transformer for attention-based sequence-to-sequence tasks like summarization

Using pandas to manipulate dataframes through screen sharing coding.

• Use pandas library in Python for data manipulation

• Share screen to demonstrate coding techniques

• Use functions like merge, groupby, and apply for data manipulation

Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data.

• Supervised learning requires labeled data for training

• Unsupervised learning does not require labeled data

• Examples of supervised learning include classification and regression

• Examples of unsupervised learning include clustering and dimensionality reduction

NLP project life cycle for sentiment analysis involves data collection, preprocessing, model training, evaluation, and deployment.

• Data collection: Gather text data from various sources like social media, reviews, or surveys.

• Data preprocessing: Clean and preprocess the text data by removing stopwords, punctuation, and special characters.

• Model training: Use machine learning or deep learning algorithms to train a sentiment analysis model on the preprocessed data.

• Evaluation: Eval...read more

P value is a measure of the strength of evidence against the null hypothesis in a statistical test, while probability is the likelihood of an event occurring.

• P value is used in hypothesis testing to determine the significance of results

• Probability is a measure of the likelihood of an event occurring

• P value ranges from 0 to 1, with lower values indicating stronger evidence against the null hypothesis

• Probability also ranges from 0 to 1, with 0 indicating impossibility and 1 ind...read more

Hypothesis testing is a statistical method used to make inferences about a population based on sample data.

• It involves formulating a hypothesis about a population parameter, collecting data, and using statistical tests to determine if the data supports or rejects the hypothesis.

• There are two types of hypotheses: null hypothesis (H0) and alternative hypothesis (H1).

• Common statistical tests for hypothesis testing include t-tests, chi-square tests, and ANOVA.

• Example: Testing if ...read more