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I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
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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
The project involved exploratory data analysis (EDA) to gain insights and identify patterns in the data.
Performed data cleaning and preprocessing
Visualized data using various charts and graphs
Identified correlations and relationships between variables
Used statistical methods to analyze data
Generated hypotheses for further analysis
Linear regression is a statistical method to model the relationship between a dependent variable and one or more independent variables.
It assumes a linear relationship between the variables
It is used to predict the value of the dependent variable based on the independent variable(s)
It can be simple linear regression (one independent variable) or multiple linear regression (more than one independent variable)
It is commo...
ML algorithms are used to train models on data to make predictions or decisions. Some popular ones are SVM, KNN, and Random Forest.
Support Vector Machines (SVM)
K-Nearest Neighbors (KNN)
Random Forest
Naive Bayes
Decision Trees
Linear Regression
Logistic Regression
Neural Networks
Gradient Boosting
Clustering Algorithms (K-Means, Hierarchical)
Association Rule Learning (Apriori)
Dimensionality Reduction Algorithms (PCA, LDA)
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