Fractal Analytics Interview Questions, Process, and Tips

Q1. Don’t remember the questions
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Q1. Cloud Native tech stack
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Q2. AWS security based questions
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Q1. Explain Transformers how different from previous RNN, LSTM etc.
Ans. 
Transformers are a type of neural network architecture that utilizes self-attention mechanisms to process sequential data.
• Transformers use self-attention mechanisms to weigh the importance of different input elements, allowing for parallel processing of sequences.

• Unlike RNNs and LSTMs, Transformers do not rely on sequential processing, making them more efficient for long-range dependencies.

• Transformers have been shown ...read more
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Q2. What are different types of Attention?
Ans. 
Different types of Attention include self-attention, global attention, and local attention.
• Self-attention focuses on relationships within the input sequence itself.

• Global attention considers the entire input sequence when making predictions.

• Local attention only attends to a subset of the input sequence at a time.

• Examples include Transformer's self-attention mechanism, Bahdanau attention, and Luong attention.
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Q3. Difference between GPT and BERT model
Ans. 
GPT is a generative model while BERT is a transformer model for natural language processing.
• GPT is a generative model that predicts the next word in a sentence based on previous words.

• BERT is a transformer model that considers the context of a word by looking at the entire sentence.

• GPT is unidirectional, while BERT is bidirectional.

• GPT is better for text generation tasks, while BERT is better for understanding the cont
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Q1. Difference between Data scientist, ML and AI
Ans. 
Data scientists analyze data to gain insights, machine learning (ML) involves algorithms that improve automatically through experience, and artificial intelligence (AI) refers to machines mimicking human cognitive functions.
• Data scientists analyze large amounts of data to uncover patterns and insights.

• Machine learning involves developing algorithms that improve automatically through experience.

• Artificial intelligence r...read more
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Python coding and ML resume based questions

Q1. Past Projects with the Director
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Q2. Behavioral Round questions Mostly
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20 MCQ questions related to Data science and 1 coding ML question.

Q1. What is overfitting and underfitting?
Ans. 
Overfitting and underfitting are common problems in machine learning where a model performs too well on training data but poorly on unseen data, or performs poorly on both training and unseen data due to oversimplification.
• Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern, leading to poor generalization on unseen data.

• Underfitting happens when a model is too simple...read more
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Q2. What is K-fold CV?
Ans. 
K-fold CV is a technique used to evaluate the performance of a machine learning model by splitting the data into k subsets.
• Data is divided into k subsets, with one subset used as the validation set and the rest as training sets.

• The process is repeated k times, with each subset used once as the validation data.

• The average of the k validation results is used as the final performance metric.

• Helps in reducing bias and vari...read more
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First round is coding round where two use cases are there. Need to solve them

Q1. They will all topics Statistics, SQL, Python, Machine Learning, Data Science
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Q1. They will discuss more on the projects what we worked on
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Q1. Salary Discussion
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