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I applied via Naukri.com and was interviewed in Nov 2022. There were 3 interview rounds.
TF-IDF is a statistical measure used to evaluate the importance of a word in a document.
TF-IDF stands for Term Frequency-Inverse Document Frequency
It is used to weigh a word's importance in a document by considering its frequency in the document and across all documents
The formula for TF-IDF is: TF-IDF = TF * IDF
TF (Term Frequency) measures how frequently a term appears in a document
IDF (Inverse Document Frequency) mea...
Group by is used to group data based on a column while window function is used to perform calculations on a specific window of data.
Group by is used to aggregate data based on a specific column
Window function is used to perform calculations on a specific window of data
Group by is used with aggregate functions like sum, count, avg, etc.
Window function is used with analytical functions like rank, lead, lag, etc.
Group by ...
Developed a predictive model to forecast customer churn for a telecom company.
Used machine learning algorithms like logistic regression and random forest.
Preprocessed and cleaned the dataset by handling missing values and outliers.
Performed feature engineering to create new variables for better model performance.
Evaluated model performance using metrics like accuracy, precision, and recall.
Implemented the model in prod
Seeking new challenges and opportunities for growth.
Looking for a more challenging role that aligns with my career goals.
Seeking a company that values innovation and encourages professional development.
Want to work in a more collaborative and diverse team environment.
Desire to explore new technologies and industries.
Current company lacks opportunities for advancement or career growth.
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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...
I applied via Company Website and was interviewed before Jan 2020. There was 1 interview round.
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...
I applied via Job Portal and was interviewed in Jan 2021. There were 3 interview rounds.
I applied via Campus Placement and was interviewed before Sep 2020. There were 3 interview rounds.
I applied via Approached by Company and was interviewed before Feb 2023. There was 1 interview round.
Hypothesis testing is a statistical method used to make inferences about a population based on sample data.
It involves formulating a hypothesis about a population parameter, collecting data, and using statistical tests to determine if the data supports or rejects the hypothesis.
There are two types of hypotheses: null hypothesis (H0) and alternative hypothesis (H1).
Common statistical tests for hypothesis testing include...
Null hypothesis is a statement that there is no significant difference or relationship between variables being studied.
Null hypothesis is typically denoted as H0 in statistical hypothesis testing.
It is the default assumption that there is no effect or relationship.
The alternative hypothesis (Ha) is the opposite of the null hypothesis.
For example, in a study testing a new drug, the null hypothesis would be that the drug...
Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data.
Supervised learning requires labeled data for training
Unsupervised learning does not require labeled data
Examples of supervised learning include classification and regression
Examples of unsupervised learning include clustering and dimensionality reduction
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