Filter interviews by
I applied via LinkedIn and was interviewed in Oct 2022. There were 4 interview rounds.
Implement a model improvement using a C++ API of Pytorch.
To rotate an image in Python, use the Pillow library's rotate() method.
Import the Image module from the Pillow library
Open the image using the open() method
Use the rotate() method to rotate the image by the desired angle
Save the rotated image using the save() method
Breadth first search problem
BFS is a graph traversal algorithm that visits all the vertices of a graph in breadth-first order
It uses a queue to keep track of the nodes to be visited next
BFS can be used to find the shortest path between two nodes in an unweighted graph
I applied via Company Website and was interviewed in Feb 2023. There were 4 interview rounds.
Some OpenCV problems
Activation functions are used to introduce non-linearity into neural networks, allowing them to learn complex patterns and relationships.
Activation functions help neural networks to learn complex patterns and relationships by introducing non-linearity.
They help in controlling the output of a neuron, ensuring that it falls within a desired range.
Common activation functions include ReLU, Sigmoid, Tanh, and Leaky ReLU.
Wit...
Learning rate is a hyperparameter that controls how much we are adjusting the weights of our network with respect to the loss gradient.
Learning rate determines the size of the steps taken during optimization.
A high learning rate can cause the model to overshoot the optimal weights, while a low learning rate can result in slow convergence.
Common learning rate values are 0.1, 0.01, 0.001, etc.
Learning rate can be adjuste...
CNN is used for image recognition while RNN is used for sequence data like text or speech.
CNN is Convolutional Neural Network, used for image recognition tasks.
RNN is Recurrent Neural Network, used for sequence data like text or speech.
CNN has convolutional layers for feature extraction, while RNN has recurrent connections for sequential data processing.
CNN is good at capturing spatial dependencies in data, while RNN i...
Yes, Logloss function is differentiable.
Logloss function is differentiable as it is a smooth and continuous function.
The derivative of Logloss function can be calculated using calculus.
Differentiability is important for optimization algorithms like gradient descent to converge smoothly.
Example: The derivative of Logloss function for binary classification is (predicted probability - actual label).
I am a business analyst with experience in data analysis and project management.
Experienced in data analysis and project management
Proficient in using tools like Excel, SQL, and Tableau
Skilled in identifying business problems and providing solutions
Excellent communication and presentation skills
Worked with cross-functional teams to achieve project goals
I am a business analyst with experience in data analysis and project management.
I have a degree in business administration
I have worked with various industries such as finance and healthcare
I am skilled in data analysis tools such as Excel and SQL
I have experience in project management and leading cross-functional teams
I am excited to join Mu Sigma because of its reputation for innovative problem-solving and data-driven approach.
Mu Sigma's focus on data-driven decision making aligns with my passion for using data to solve complex business problems.
I am impressed by Mu Sigma's track record of delivering impactful solutions for clients across various industries.
I am excited about the opportunity to work with a diverse team of talented ...
Mu Sigma is a data analytics and decision sciences company that helps businesses make data-driven decisions.
Mu Sigma provides services such as data engineering, data science, decision sciences, and design thinking.
They work with clients across various industries including healthcare, retail, finance, and technology.
Mu Sigma's solutions help clients improve their operations, optimize their marketing strategies, and enha...
based on 2 interviews
Interview experience
based on 12 reviews
Rating in categories
Computer Vision Engineer
6
salaries
| ₹0 L/yr - ₹0 L/yr |
Field Engineer
4
salaries
| ₹0 L/yr - ₹0 L/yr |
Machine Learning Engineer
4
salaries
| ₹0 L/yr - ₹0 L/yr |
Software Engineer
3
salaries
| ₹0 L/yr - ₹0 L/yr |
Product Designer
3
salaries
| ₹0 L/yr - ₹0 L/yr |
Fractal Analytics
Mu Sigma
Tiger Analytics
Algonomy