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Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.
Precision is calculated as TP / (TP + FP), where TP is true positives and FP is false positives.
It measures the accuracy of positive predictions made by the model.
A high precision indicates that the model is good at predicting positive cases without many false positives.
For example, in a binary classificatio...
A large language model is a type of artificial intelligence model that is capable of understanding and generating human language at a large scale.
Large language models use deep learning techniques to process and generate text.
Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).
I applied via Campus Placement and was interviewed before Jul 2023. There were 3 interview rounds.
Mostly data related question and two coding questions which we had to do in python only
Attention in data science refers to the mechanism that allows models to focus on specific parts of the input data.
Attention mechanisms help models to weigh the importance of different input features.
They are commonly used in natural language processing tasks such as machine translation and text summarization.
Attention can improve the performance of models by allowing them to selectively focus on relevant information.
Ex...
Efficiency of LLMs can be judged based on various factors such as accuracy, speed, resource consumption, and interpretability.
Evaluate accuracy by comparing LLM predictions with ground truth labels
Assess speed by measuring the time taken for LLM to process data
Analyze resource consumption in terms of memory and computational power usage
Consider interpretability by examining how easily LLM decisions can be understood
Use...
I applied via Campus Placement and was interviewed before Jul 2023. There were 2 interview rounds.
Hacker Rank Test on coding questions
KNN is a supervised learning algorithm used for classification and regression, while Kmeans is an unsupervised clustering algorithm.
KNN is a supervised learning algorithm that classifies a new data point based on the majority class of its k-nearest neighbors.
Kmeans is an unsupervised clustering algorithm that partitions data into k clusters based on similarity.
KNN requires labeled training data, while Kmeans does not r...
Coding a training pipeline involves creating a process to train machine learning models efficiently.
Define the data preprocessing steps
Split the data into training and validation sets
Choose a machine learning algorithm to train the model
Tune hyperparameters to optimize model performance
Evaluate the model using metrics like accuracy or loss
I applied via Campus Placement and was interviewed before Oct 2022. There were 4 interview rounds.
Basic leet code questions easy to a bit of medium
Handling class imbalance involves techniques like resampling, using different algorithms, and adjusting class weights.
Use resampling techniques like oversampling the minority class or undersampling the majority class.
Try using different algorithms that are less sensitive to class imbalance, such as Random Forest or XGBoost.
Adjust class weights in the model to give more importance to the minority class.
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Code for parsing a triangle
Use a loop to iterate through each line of the triangle
Split each line into an array of numbers
Store the parsed numbers in a 2D array or a list of lists
The ASCII value is a numerical representation of a character. It includes both capital and small alphabets.
ASCII values range from 65 to 90 for capital letters A to Z.
ASCII values range from 97 to 122 for small letters a to z.
For example, the ASCII value of 'A' is 65 and the ASCII value of 'a' is 97.
Coding round basic packages , and basic python coding
I have worked on projects involving predictive modeling, natural language processing, and computer vision.
Predictive modeling: Developed machine learning models to predict customer churn for a telecom company.
Natural language processing: Built a sentiment analysis tool to analyze customer reviews for a retail company.
Computer vision: Implemented a facial recognition system for access control in a secure facility.
I applied via Recruitment Consultant and was interviewed in Mar 2021. There was 1 interview round.
I applied via Approached by Company and was interviewed in Aug 2023. There were 3 interview rounds.
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