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Bluebird Solar Interview Questions and Answers
Q1. What is linear regression and logistics regression?
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 variables, while logistic regression uses a logistic funct...read more
Q2. What is central limit theorem? Why we use it
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, if we take multiple samples of a population and calculat...read more
Q3. What is support vector machine?
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, polynomial, and radial basis function kernels
Q4. Difference between Random and ordering partition
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 partition is helpful for time series data analysis or when data n...read more
Q5. Difference between Logistic and Linear Regression
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 regression uses a linear function.
Logistic regression is commonly u...read more
Q6. What is linear and logistics.?
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 is assumed to be linear, while in logistic regression, th...read more
Q7. Difference between KNN and K Means
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 is a lazy learner as it does not learn a discriminative fu...read more
Q8. Range of Cross Entropy Loss
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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