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posted on 28 Jun 2024
Kubernetes on GKE is a managed Kubernetes service provided by Google Cloud Platform.
GKE stands for Google Kubernetes Engine.
It allows users to deploy, manage, and scale containerized applications using Kubernetes.
GKE provides features such as automatic scaling, monitoring, and logging.
Users can easily create Kubernetes clusters on GKE using the Google Cloud Console or command-line tools.
GKE integrates with other Google...
Yes, Application Servers are software frameworks that provide an environment for running web applications.
Application Servers manage the execution of web applications
They provide services such as security, scalability, and resource management
Examples include Apache Tomcat, JBoss, and Microsoft IIS
Google Cloud is a suite of cloud computing services provided by Google.
Offers a wide range of services including computing, storage, networking, machine learning, and more
Provides tools for data analytics, machine learning, and artificial intelligence
Allows users to build, test, and deploy applications on Google's infrastructure
Offers scalable and flexible pricing options based on usage
Examples: Google Compute Engine,
BigQuery architecture is a serverless, highly scalable, and cost-effective data warehouse designed for big data analytics.
BigQuery separates storage and compute, allowing for independent scaling of each
It uses a distributed architecture to process queries in parallel for fast results
Data is stored in Capacitor, a proprietary storage format optimized for analytical processing
Top trending discussions
Forecasting problem - Predict daily sku level sales
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
Bias is the error introduced by approximating a real-world problem, leading to underfitting.
Variance is the error introduced by modeling the noise in the training data, leading to overfitting.
High bias can cause a model to miss relevant relationships between features and target variable.
High variance can cause a model to ...
Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.
Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.
Examples of parametric models inc...
I applied via Recruitment Consultant and was interviewed before Oct 2020. There were 3 interview rounds.
posted on 6 Nov 2015
I applied via Naukri.com and was interviewed in Jan 2023. There were 2 interview rounds.
posted on 19 Mar 2025
I appeared for an interview before Mar 2024, where I was asked the following questions.
I admire the company's innovative approach and commitment to excellence, aligning with my career goals and values.
The company's focus on cutting-edge technology resonates with my passion for continuous learning and growth.
I am impressed by the collaborative culture here, which fosters teamwork and creativity, as seen in your recent project on XYZ.
The opportunity to work on impactful projects that improve user experienc...
I expect collaboration, innovation, and growth opportunities within the DataflowGroup.
Collaboration: I hope to work closely with cross-functional teams to enhance data processing workflows.
Innovation: I expect to contribute to innovative solutions that improve data handling and processing efficiency.
Growth Opportunities: I look forward to mentorship and professional development to advance my skills in data engineering.
...
=== compares value and type, while == only compares value
=== is stricter than == in type checking
=== returns true only if both operands are of the same type and have the same value
== performs type coercion, which can lead to unexpected results
For example, '5' == 5 returns true, but '5' === 5 returns false
I applied via Naukri.com and was interviewed in Mar 2022. There was 1 interview round.
based on 1 interview
Interview experience
Data Scientist
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| ₹12 L/yr - ₹18 L/yr |
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