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I have used tools like Flask, Docker, and AWS to deploy machine learning models.
Utilized Flask to create RESTful APIs for model deployment
Containerized models using Docker for easy deployment and scalability
Deployed models on AWS EC2 instances for production use
Transformers are a type of deep learning model architecture that utilizes self-attention mechanisms.
Transformers consist of an encoder and a decoder, each composed of multiple layers of self-attention and feedforward neural networks.
Self-attention allows the model to weigh the importance of different input tokens when making predictions.
Transformers have been widely used in natural language processing tasks, such as ma...
I applied via Recruitment Consultant and was interviewed in Mar 2021. There was 1 interview round.
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.
I applied via Referral and was interviewed in Mar 2021. There were 4 interview rounds.
Data science is the field of extracting insights and knowledge from data using various techniques and tools.
Data science involves collecting, cleaning, and analyzing data to extract insights.
It uses various techniques such as machine learning, statistical modeling, and data visualization.
Data science is used in various fields such as finance, healthcare, and marketing.
Examples of data science applications include fraud...
Python and R are programming languages commonly used in data science and statistical analysis.
Python is a general-purpose language with a large community and many libraries for data manipulation and machine learning.
R is a language specifically designed for statistical computing and graphics, with a wide range of packages for data analysis and visualization.
Both languages are popular choices for data scientists and hav...
posted on 28 Feb 2024
I applied via Naukri.com and was interviewed before Feb 2023. There were 2 interview rounds.
PCA is used to reduce the dimensionality of data by finding the most important features.
PCA is used when dealing with high-dimensional data to reduce the number of features and avoid multicollinearity.
It helps in visualizing data in lower dimensions while retaining as much variance as possible.
PCA is commonly used in image processing, genetics, finance, and other fields where dimensionality reduction is needed.
I applied via Approached by Company and was interviewed in Jan 2024. There was 1 interview round.
Model evaluation is crucial in ML pipeline to assess the performance and generalization of the model.
Helps in selecting the best model for the given problem by comparing different models based on metrics like accuracy, precision, recall, etc.
Prevents overfitting by checking if the model is performing well on unseen data.
Guides in fine-tuning hyperparameters to improve model performance.
Enables understanding of model li...
I applied via Company Website and was interviewed in Apr 2024. There was 1 interview round.
Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.
Linear regression is used to predict the value of a dependent variable based on the value of one or more independent variables.
It assumes a linear relationship between the independent and dependent variables.
The goal of linear regression is to find the best-fitting line that minimi...
Count the number of duplicate words in a string.
Split the string into words using a delimiter like space or punctuation.
Create a dictionary to store the count of each word.
Iterate through the words and increment the count in the dictionary.
Count the number of words with count greater than 1 as duplicates.
Chunking in LLM refers to breaking down text into smaller chunks for better processing by the language model.
Chunking helps improve the efficiency of the language model by breaking down large text inputs into smaller segments.
It can help the model better understand the context and relationships within the text.
Chunking is commonly used in natural language processing tasks such as text summarization and sentiment analys
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Senior Associate
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Software Engineer
12
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Senior Software Engineer
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Process Associate
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