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My weakness is that I tend to get too focused on details, sometimes causing me to lose sight of the bigger picture.
I have a tendency to spend too much time on minor details
I sometimes struggle with prioritizing tasks and can get overwhelmed
I am working on improving my time management skills to balance detail-oriented work with broader goals
I applied via LinkedIn and was interviewed before Mar 2023. There was 1 interview round.
Data-driven business involves using data to make informed decisions and drive strategies.
Using data to analyze trends and patterns in customer behavior
Utilizing data to optimize marketing campaigns and target specific demographics
Implementing data-driven decision-making processes to improve operational efficiency
Leveraging data to forecast sales and inventory needs
Measuring key performance indicators (KPIs) to track bu
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posted on 29 Nov 2024
I applied via Naukri.com and was interviewed before Nov 2023. There were 4 interview rounds.
Developed a machine learning model to predict customer churn for a telecom company.
Collected and cleaned customer data including usage patterns and demographics
Used classification algorithms like Random Forest and Logistic Regression to build the model
Evaluated model performance using metrics like accuracy, precision, and recall
Math, English, reasoning
I applied via Recruitment Consultant and was interviewed in Jul 2021. There was 1 interview round.
I have used various algorithms such as linear regression, decision trees, and neural networks to analyze data and make predictions.
Used linear regression to predict housing prices based on various features
Implemented decision trees to classify customer behavior and recommend products
Utilized neural networks for image recognition tasks
Challenges included dealing with missing data and overfitting
Outcome was improved accu
The algorithm was chosen based on its ability to handle large datasets and its accuracy in predicting outcomes.
The algorithm was selected after evaluating its performance on similar datasets.
It was chosen for its ability to handle high-dimensional data and its scalability.
The algorithm was compared to other models and found to have the highest accuracy in predicting outcomes.
The choice of algorithm also depends on the
I am a data analyst with a strong background in statistics and data visualization.
Experienced in analyzing large datasets to extract valuable insights
Proficient in statistical analysis and data visualization tools such as Python, R, and Tableau
Strong problem-solving skills and attention to detail
Excellent communication skills to present findings to stakeholders
My city is a vibrant and diverse urban center with a rich history and cultural heritage.
Located in the northeastern region of the country
Known for its historic landmarks such as the Old Town Square and Cathedral
Home to a thriving arts and music scene
Diverse population with a mix of different ethnicities and cultures
I am a data analyst with a strong background in statistics and data visualization.
Experienced in analyzing large datasets to extract valuable insights
Proficient in using statistical tools such as R and Python
Skilled in creating interactive dashboards using Tableau
Strong communication skills to present findings to stakeholders
I have 3 years of experience as a Data Analyst in a tech company.
Analyzed large datasets to extract valuable insights
Created visualizations and reports to communicate findings
Collaborated with cross-functional teams to drive data-driven decision making
I applied via Naukri.com and was interviewed before Feb 2023. There were 2 interview rounds.
LSTM is a type of RNN that addresses the vanishing gradient problem by using memory cells.
RNN stands for Recurrent Neural Network, a type of neural network that processes sequential data.
LSTM stands for Long Short-Term Memory, a type of RNN that includes memory cells to retain information over long sequences.
LSTM is designed to overcome the vanishing gradient problem, which occurs when training RNNs on long sequences.
L...
Evaluation matrices are used to assess the performance of models in data science.
Confusion matrix: used to evaluate the performance of classification models.
Precision, recall, and F1 score: measures for binary classification models.
Mean squared error (MSE): evaluates the performance of regression models.
R-squared: assesses the goodness of fit for regression models.
Area under the ROC curve (AUC-ROC): evaluates the perfo...
The test was psychometric and aptitude. Interview was easy.
Generative AI is a powerful technology that can create new content based on existing data.
Generative AI uses neural networks to generate new content such as images, text, and music.
It has applications in various fields like art, music composition, and even creating realistic deepfake videos.
Examples include OpenAI's GPT-3 for text generation and DeepDream for image generation.
I applied via Job Fair and was interviewed in May 2024. There was 1 interview round.
I have learned multiple programming languages including Python, R, SQL, and Java.
Python
R
SQL
Java
I applied via Campus Placement and was interviewed before Jul 2023. There were 3 interview rounds.
It was campus placement. We were givien the topic "future of AI and ML in automobile industry". The time given was around 15mins. The explained the process in great detail and very clearly.
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