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I applied via Campus Placement
Test+2 interviews(technical and statistics)
Basic guestimates and case studies
Aptitude, coding on python NLP
Python Data Frames, String list manipulation
Python questions moderate to difficult
I am a data scientist with a background in statistics and machine learning.
I have a Master's degree in Data Science from XYZ University.
I have experience working with Python, R, and SQL for data analysis.
I have worked on projects involving predictive modeling and data visualization.
I am passionate about using data to drive business decisions and solve complex problems.
SQL, Python and Apti ques
Seeking new challenges and growth opportunities in a different environment.
Looking for new challenges to enhance my skills and knowledge
Seeking growth opportunities that align with my career goals
Interested in exploring different work environments and cultures
I applied via Referral and was interviewed in Sep 2024. There was 1 interview round.
Asked 2 to 3 python coding question...
I applied via Job Portal
Random forest is an ensemble learning method used for classification and regression tasks.
Random forest is a collection of decision trees that are trained on random subsets of the data.
Each tree in the random forest independently predicts the target variable, and the final prediction is made by averaging the predictions of all trees.
Random forest is robust to overfitting and noisy data, and can handle large datasets wi...
Lasso is a feature selection technique that penalizes the absolute size of the regression coefficients.
Lasso stands for Least Absolute Shrinkage and Selection Operator
It adds a penalty term to the regression equation, forcing some coefficients to be exactly zero
Helps in selecting the most important features and reducing overfitting
Useful when dealing with high-dimensional data
Example: In a dataset with multiple feature...
I applied via Naukri.com and was interviewed in Apr 2022. There were 3 interview rounds.
I applied via Referral and was interviewed in Aug 2022. There were 3 interview rounds.
Relevant projects in Data Science and expertise in tools and technologies
Projects: Predictive modeling, Natural Language Processing, Computer Vision, Recommender Systems, Time Series Analysis
Tools: Python, R, SQL, Tableau, Hadoop, Spark, TensorFlow, Keras, Scikit-learn
Technologies: Machine Learning, Deep Learning, Big Data, Cloud Computing, Data Visualization
I applied via LinkedIn and was interviewed in Feb 2023. There were 6 interview rounds.
Platform HackerEarth
9 Questions
2 Coding Questions on Python based on Dynamic Programming
7 Questions MCQ on Data Science and SQL
based on 1 interview
Interview experience
based on 7 reviews
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