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I applied via Campus Placement and was interviewed in Mar 2024. There was 1 interview round.
UI/UX components are building blocks used in designing user interfaces and experiences.
UI components are visual elements like buttons, input fields, and menus that users interact with.
UX components focus on the overall user experience, including navigation, information architecture, and usability.
Examples of UI components include dropdown menus, sliders, and checkboxes.
Examples of UX components include user flows, wire
I have worked on a variety of technologies including Java, Python, SQL, HTML, CSS, JavaScript, and Git.
Java
Python
SQL
HTML
CSS
JavaScript
Git
posted on 14 May 2022
I applied via Walk-in and was interviewed before May 2021. There were 3 interview rounds.
posted on 10 Nov 2022
Basic maths and logic aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
posted on 11 May 2023
I applied via Job Fair and was interviewed in Apr 2023. There were 3 interview rounds.
It was on Coder Byte , Easy String question
posted on 21 Jul 2024
posted on 22 Nov 2024
I applied via Campus Placement and was interviewed in Oct 2024. There were 2 interview rounds.
Reasoning , maths , coding, english
Java python css c programming sql, html.
I applied via Campus Placement and was interviewed in Mar 2024. There was 1 interview round.
Hyperparameter tuning is the process of selecting the best set of hyperparameters for a machine learning model.
Hyperparameters are parameters that are set before the learning process begins.
Hyperparameter tuning involves adjusting hyperparameters to optimize the model's performance.
Common techniques for hyperparameter tuning include grid search, random search, and Bayesian optimization.
Neural networks are trained using algorithms that adjust the weights and biases of the network based on the input data and desired output.
Neural networks are trained using a process called backpropagation, where the error between the predicted output and the actual output is used to adjust the weights and biases of the network.
Training data is fed into the neural network, and the network's output is compared to the des...
Overfitting occurs when a machine learning model learns the training data too well, including noise and outliers, leading to poor generalization on new data.
Overfitting happens when a model is too complex and captures noise in the training data.
It can be identified when a model performs well on training data but poorly on unseen data.
Techniques to prevent overfitting include cross-validation, regularization, and early ...
based on 2 interviews
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