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IBM
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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.
DSA,ML,SQL,stats,DL,
What people are saying about IBM
I applied via Company Website and was interviewed in Nov 2024. There was 1 interview round.
Its really easy if you know python well
IBM interview questions for designations
60 min hackerrank test,with one mysql medium difficulty question and one python medium/little hard level difficulty
Get interview-ready with Top IBM Interview Questions
I applied via Company Website and was interviewed in Nov 2023. There was 1 interview round.
I applied via Job Portal and was interviewed before Feb 2023. There was 1 interview round.
Hyperparameters in random forest are parameters that are set before the learning process begins.
Hyperparameters control the behavior of the random forest algorithm.
They are set by the data scientist and are not learned from the data.
Examples of hyperparameters in random forest include the number of trees, the maximum depth of trees, and the number of features considered at each split.
A QnA system with LLM is a system that uses the Language Model for Information Retrieval and Question Answering.
Preprocess the input question and convert it into a format suitable for the LLM model.
Fine-tune the LLM model on a dataset of question-answer pairs.
Use the fine-tuned model to generate answers for new questions.
Evaluate the performance of the QnA system using metrics like precision, recall, and F1 score.
Itera...
Unit testing is a process of testing individual units of code to ensure they function correctly.
Write test cases for each unit of code
Test inputs, outputs, and edge cases
Use testing frameworks like JUnit or pytest
Automate tests to run regularly
Ensure tests are independent, isolated, and repeatable
I applied via Company Website and was interviewed before Dec 2023. There were 2 interview rounds.
It was of hackerrank and 2 question
PCA is a dimensionality reduction technique, decision tree is a classification algorithm, and computer vision is a field of study focused on enabling computers to interpret and understand visual information.
PCA is used to reduce the number of variables in a dataset while retaining the most important information.
Decision trees are used to classify data based on a set of rules and conditions.
Computer vision involves usin...
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.
Boosting involves training multiple models sequentially, where each subsequent model c...
Parameters of a Decision Tree include max depth, min samples split, criterion, and splitter.
Max depth: maximum depth of the tree
Min samples split: minimum number of samples required to split an internal node
Criterion: function to measure the quality of a split (e.g. 'gini' or 'entropy')
Splitter: strategy used to choose the split at each node (e.g. 'best' or 'random')
Developed a predictive model to forecast 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
Provided actionable insights to the company to reduce customer churn rate
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