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I appeared for an interview in Dec 2024.
I know this company through researching online, reading reviews, and speaking with current employees.
Researched online about the company's history, values, and products/services
Read reviews from current and former employees on websites like Glassdoor
Spoke with current employees to learn more about the company culture and work environment
I have 3 years of experience as a Packing Operator and I am seeking a similar position in this company.
I have 3 years of experience as a Packing Operator in a manufacturing company
I am skilled in operating packing machinery and ensuring product quality
I am familiar with following safety protocols and maintaining a clean work environment
The company expects high attention to detail, efficiency, teamwork, and adherence to safety protocols.
High attention to detail in packing products accurately
Efficiently operate packaging machinery
Work well in a team environment
Follow safety protocols to prevent accidents
Maintain cleanliness and organization in the packing area
I have been working with your company for 3 years and feel like a valued member of the team.
I have been with the company for 3 years
I feel like a valued member of the team
I enjoy working with my colleagues and feel supported by them
I applied via LinkedIn and was interviewed before Jan 2021. There were 5 interview rounds.
I applied via Recruitment Consulltant and was interviewed before Mar 2021. There were 2 interview rounds.
Job related questions
Top trending discussions
I applied via Referral and was interviewed in Feb 2020. There were 6 interview rounds.
I applied via Recruitment Consultant and was interviewed before May 2020. There were 3 interview rounds.
Clone a linked list with random pointers.
Create a new node for each node in the original list.
Store the mapping between the original and cloned nodes in a hash table.
Traverse the original list again and set the random pointers in the cloned list using the hash table.
Return the head of the cloned list.
I applied via Campus Placement and was interviewed in Nov 2022. There were 5 interview rounds.
This is the aptitude round in this round quant questions were asked
In this round 2 java coding questions were there
A framework is a set of rules, guidelines, and standards that provide a structure for developing software applications.
A framework provides a common structure for developers to work within
It includes pre-written code and libraries that can be used to speed up development
Frameworks can be specific to a programming language or platform
Examples include AngularJS, React, and Ruby on Rails
Java is a widely used programming language known for its platform independence and object-oriented approach.
Java is an object-oriented language that follows the 'write once, run anywhere' principle.
It is used for developing a wide range of applications, from desktop to web and mobile applications.
Java programs are compiled into bytecode that can run on any Java Virtual Machine (JVM).
It provides built-in libraries and f...
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 3 interviews
Interview experience
based on 37 reviews
Rating in categories
Hyderabad / Secunderabad,
Chennai
+18-13 Yrs
₹ 0.8-1.5 LPA
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