Feynn Labs Data Science Intern Interview Questions, Process, and Tips

Q1. What is random forest? What it is called random?
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Q2. What is svm? Any project you perform using this?
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Q1. Difference between Random and ordering partition
Ans. 
Random partition involves splitting data randomly, while ordering partition involves splitting data based on a specific order.
• Random partition randomly divides data into subsets without any specific order.

• Ordering partition divides data into subsets based on a specific order, such as time or alphabetical order.

• Random partition is useful for creating training and testing sets for machine learning models.

• Ordering partiti...read more
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Q2. Difference between Logistic and Linear Regression
Ans. 
Logistic regression is used for binary classification while linear regression is used for regression tasks.
• Logistic regression predicts the probability of a binary outcome (0 or 1) based on one or more independent variables.

• Linear regression predicts a continuous outcome based on one or more independent variables.

• Logistic regression uses a sigmoid function to map predicted values between 0 and 1, while linear regressio...read more
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Q3. Difference between KNN and K Means
Ans. 
KNN is a supervised learning algorithm used for classification and regression, while K Means is an unsupervised clustering algorithm.
• KNN stands for K-Nearest Neighbors and assigns a class label based on majority voting of its k-nearest neighbors.

• K Means is a clustering algorithm that partitions data into k clusters based on similarity.

• KNN requires labeled data for training, while K Means does not need labeled data.

• KNN ...read more
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Q4. Range of Cross Entropy Loss
Ans. 
Cross entropy loss measures the difference between two probability distributions.
• Range of cross entropy loss is [0, infinity)

• Lower values indicate better model performance

• Commonly used in classification tasks
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Q1. Introduced yourself.?
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Q2. What is linear and logistics.?
Ans. 
Linear regression is a statistical method to model the relationship between a dependent variable and one or more independent variables. Logistic regression is used to model the probability of a binary outcome.
• Linear regression is used for predicting continuous outcomes, while logistic regression is used for predicting binary outcomes.

• In linear regression, the relationship between the independent and dependent variables...read more
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Data Science Project

Q1. What is linear regression and logistics regression?
Ans. 
Linear regression is a statistical method to model the relationship between a dependent variable and one or more independent variables. Logistic regression is used to model the probability of a binary outcome.
• Linear regression is used for predicting continuous outcomes, while logistic regression is used for predicting binary outcomes.

• Linear regression assumes a linear relationship between the independent and dependent ...read more
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Q2. What is central limit theorem? Why we use it
Ans. 
Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
• Central Limit Theorem is used to make inferences about a population mean based on the sample mean.

• It allows us to use the properties of the normal distribution to estimate population parameters.

• It is essential in hypothesis testing and constructing confidence intervals.

• For example...read more
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Q3. What is support vector machine?
Ans. 
Support Vector Machine is a supervised machine learning algorithm used for classification and regression tasks.
• Support Vector Machine finds the hyperplane that best separates different classes in the feature space

• It works by maximizing the margin between the hyperplane and the nearest data points, known as support vectors

• SVM can handle both linear and non-linear data by using different kernel functions like linear, pol
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