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I applied via Naukri.com and was interviewed in Jul 2024. There were 3 interview rounds.
I have worked on a project predicting housing prices using regression models on Kaggle.
Used Python libraries like Pandas, NumPy, and Scikit-learn for data preprocessing and modeling
Performed feature engineering to improve model performance
Evaluated model performance using metrics like RMSE and MAE
CNN stands for Convolutional Neural Networks, a type of deep learning algorithm commonly used for image recognition.
CNNs are designed to automatically and adaptively learn spatial hierarchies of features from data.
They consist of multiple layers of convolutional, pooling, and fully connected layers.
CNNs have been widely used in computer vision tasks such as image classification, object detection, and facial recognition...
PCA is a dimensionality reduction technique used to transform high-dimensional data into a lower-dimensional space while preserving the most important information.
PCA helps in identifying patterns in data by reducing the number of variables
It finds the directions (principal components) along which the variance of the data is maximized
PCA is commonly used in image processing, genetics, and finance
Central limit theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
Central limit theorem is a fundamental concept in statistics.
It states that the sampling distribution of the sample mean will be approximately normally distributed, regardless of the shape of the population distribution.
It is important for making inferences about population parame...
Random Forest is an ensemble learning algorithm that builds multiple decision trees and combines their predictions.
Random Forest is a supervised learning algorithm used for classification and regression tasks.
It creates a forest of decision trees during training, where each tree is built using a random subset of features and data points.
The final prediction is made by aggregating the predictions of all the individual t...
Pruning is a technique used in machine learning to reduce the size of decision trees by removing unnecessary branches.
Pruning helps prevent overfitting by simplifying the model
There are two types of pruning: pre-pruning and post-pruning
Pre-pruning involves setting a limit on the depth of the tree or the number of leaf nodes
Post-pruning involves removing branches that do not improve the overall accuracy of the tree
Examp...
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I applied via campus placement at Indian Institute of Technology (IIT), Mandi and was interviewed before Jan 2024. There was 1 interview round.
I applied via Naukri.com and was interviewed in Dec 2024. There were 3 interview rounds.
This was good aptitude test computer based
Coding round share screen and code
I applied via Approached by Company and was interviewed in Aug 2024. There were 2 interview rounds.
*****, arjumpudi satyanarayana
Python is a high-level programming language known for its simplicity and readability.
Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.
It emphasizes code readability and uses indentation for block delimiters.
Python has a large standard library and a vibrant community of developers.
Example: print('Hello, World!')
Example: import pandas as pd
Code problems refer to issues or errors in the code that need to be identified and fixed.
Code problems can include syntax errors, logical errors, or performance issues.
Examples of code problems include missing semicolons, incorrect variable assignments, or inefficient algorithms.
Identifying and resolving code problems is a key skill for data scientists to ensure accurate and efficient data analysis.
Python code is a programming language used for data analysis, machine learning, and scientific computing.
Python code is written in a text editor or an integrated development environment (IDE)
Python code is executed using a Python interpreter
Python code can be used for data manipulation, visualization, and modeling
The project is a machine learning model to predict customer churn for a telecommunications company.
Developing predictive models using machine learning algorithms
Analyzing customer data to identify patterns and trends
Evaluating model performance and making recommendations for reducing customer churn
The question seems to be incomplete or misspelled.
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Ask for clarification or context to provide a relevant answer.
I applied via Naukri.com and was interviewed in Jul 2024. There were 2 interview rounds.
I am a data scientist with a background in statistics and machine learning, passionate about solving complex problems using data-driven approaches.
Background in statistics and machine learning
Experience in solving complex problems using data-driven approaches
Passionate about leveraging data to drive insights and decision-making
Developed a predictive model for customer churn in a telecom company.
Collected and cleaned customer data including usage patterns and demographics.
Used machine learning algorithms such as logistic regression and random forest to build the model.
Evaluated model performance using metrics like accuracy, precision, and recall.
Implemented the model into the company's CRM system for real-time predictions.
I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
Context window in LLMs refers to the number of surrounding words considered when predicting the next word in a sequence.
Context window helps LLMs capture dependencies between words in a sentence.
A larger context window allows the model to consider more context but may lead to increased computational complexity.
For example, in a context window of 2, the model considers 2 words before and 2 words after the target word fo
top_k parameter is used to specify the number of top elements to be returned in a result set.
top_k parameter is commonly used in machine learning algorithms to limit the number of predictions or recommendations.
For example, in recommendation systems, setting top_k=5 will return the top 5 recommended items for a user.
In natural language processing tasks, top_k can be used to limit the number of possible next words in a
Regex patterns in Python are sequences of characters that define a search pattern.
Regex patterns are used for pattern matching and searching in strings.
They are created using the 're' module in Python.
Examples of regex patterns include searching for email addresses, phone numbers, or specific words in a text.
Iterators are objects that allow iteration over a sequence of elements. Tuples are immutable sequences of elements.
Iterators are used to loop through elements in a collection, like lists or dictionaries
Tuples are similar to lists but are immutable, meaning their elements cannot be changed
Example of iterator: for item in list: print(item)
Example of tuple: my_tuple = (1, 2, 3)
Yes, I have experience working with REST APIs in various projects.
Developed RESTful APIs using Python Flask framework
Consumed REST APIs in data analysis projects using requests library
Used Postman for testing and debugging REST APIs
I applied via Recruitment Consulltant and was interviewed in Jul 2024. There were 3 interview rounds.
Numpy,pandas,data analysis
Expect technical questions as well as moderate level coding questions
Time structure is a part of Environment that used as reference to measure and keep track . The structure of the time also a central . And overall the structure of time remains of the debate.
Mathematics and other questions
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