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I applied via Job Portal and was interviewed in Sep 2023. There was 1 interview round.
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The zip function in Python is used to combine multiple iterables into a single iterable of tuples.
Zip function takes two or more iterables as arguments and returns an iterator of tuples where the i-th tuple contains the i-th element from each of the input iterables.
If the input iterables are of different lengths, the resulting iterator will only have as many elements as the shortest input iterable.
Example: zip([1, 2, 3...
NLP (Natural Language Processing) in machine learning is the ability of a computer to understand, interpret, and generate human language.
NLP enables machines to analyze and derive meaning from human language data.
It involves tasks such as text classification, sentiment analysis, named entity recognition, and machine translation.
Examples of NLP applications include chatbots, language translation services, and speech rec
I applied via Company Website and was interviewed in Apr 2024. There was 1 interview round.
Types of prompts include text prompts, image prompts, audio prompts, and video prompts.
Text prompts: prompts that are in written form
Image prompts: prompts that are in visual form
Audio prompts: prompts that are in audio form
Video prompts: prompts that are in video form
Symmetric encryption uses the same key for both encryption and decryption, while asymmetric encryption uses different keys for encryption and decryption.
Symmetric encryption is faster and more efficient than asymmetric encryption.
Asymmetric encryption provides better security as it uses a public key for encryption and a private key for decryption.
Examples of symmetric encryption algorithms include AES and DES, while ex...
I applied via Company Website and was interviewed in Jul 2023. There were 4 interview rounds.
Python basic coding questions (pandas, numpy, OOPs concept.
AI ML theory questions
I applied via Referral and was interviewed in Jul 2024. There were 3 interview rounds.
30 MCQs where 15 Need to be answered correctly to get shortlisted.
Sanfoundary source is very helpful in cracking it.
Oops concepts refer to Object-Oriented Programming principles such as Inheritance, Encapsulation, Polymorphism, and Abstraction.
Inheritance: Allows a class to inherit properties and behavior from another class.
Encapsulation: Bundling data and methods that operate on the data into a single unit.
Polymorphism: Ability to present the same interface for different data types.
Abstraction: Hiding the complex implementation det
File handling refers to the process of managing and manipulating files on a computer system.
File handling involves tasks such as creating, reading, writing, updating, and deleting files.
Common file operations include opening a file, reading its contents, writing data to it, and closing the file.
File handling in programming languages often involves using functions or libraries specifically designed for file operations.
E...
Supervised learning uses labeled data to train a model, while unsupervised learning finds patterns in unlabeled data.
Supervised learning requires input-output pairs for training
Examples include linear regression, support vector machines, and neural networks
Unsupervised learning clusters data based on similarities or patterns
Examples include k-means clustering, hierarchical clustering, and principal component analysis
I applied via Approached by Company and was interviewed in Jul 2024. There were 2 interview rounds.
Developed a recommendation system for an e-commerce platform using collaborative filtering
Used collaborative filtering to analyze user behavior and recommend products
Implemented matrix factorization techniques to improve recommendation accuracy
Evaluated model performance using metrics like RMSE and precision-recall curves
I am currently working on developing machine learning models using Python, TensorFlow, and scikit-learn.
Python programming language
TensorFlow framework
scikit-learn library
I would approach a machine learning problem by first understanding the problem, collecting and preprocessing data, selecting a suitable algorithm, training the model, evaluating its performance, and fine-tuning it.
Understand the problem statement and define the objectives clearly.
Collect and preprocess the data to make it suitable for training.
Select a suitable machine learning algorithm based on the problem type (clas...
I was interviewed in Oct 2024.
OHE is a technique used in machine learning to convert categorical data into a binary format.
OHE is used to convert categorical variables into a format that can be provided to ML algorithms.
Each category is represented by a binary vector where only one element is 'hot' (1) and the rest are 'cold' (0).
For example, if we have a 'color' feature with categories 'red', 'blue', 'green', OHE would represent them as [1, 0, 0],
Conditional probability is the likelihood of an event occurring given that another event has already occurred.
Conditional probability is calculated using the formula P(A|B) = P(A and B) / P(B)
It represents the probability of event A happening, given that event B has already occurred
Conditional probability is used in various fields such as machine learning, statistics, and finance
Precision and recall are evaluation metrics used in machine learning to measure the performance of a classification model.
Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.
Recall is the ratio of correctly predicted positive observations to the all observations in actual class.
Precision is important when the cost of false positives is high, while recall is i...
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