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Overloading is the ability to define multiple methods with the same name but different parameters.
Overloading allows for more flexibility in method naming and improves code readability.
Examples include defining multiple constructors for a class with different parameter lists or defining a method that can accept different data types as input.
Overloading is resolved at compile-time based on the number and types of a...
To find unique keys in 2 dictionaries.
Create a set of keys for each dictionary
Use set operations to find the unique keys
Return the unique keys
AWS EC2 model deployment involves creating an instance, installing necessary software, and deploying the model.
Create an EC2 instance with the desired specifications
Install necessary software and dependencies on the instance
Upload the model and any required data to the instance
Deploy the model using a web server or API
Monitor the instance and model performance for optimization
Finding index of 2 numbers having total equal to target in a list without nested for loop.
Use dictionary to store the difference between target and each element of list.
Iterate through list and check if element is in dictionary.
Return the indices of the two elements that add up to target.
Python dictionaries are versatile data structures for storing key-value pairs, enabling efficient data retrieval and manipulation.
Dictionaries are created using curly braces: example = {'key': 'value'}
Access values using keys: example['key'] returns 'value'.
Dictionaries are mutable; you can add or remove items: example['new_key'] = 'new_value'.
Keys must be unique and immutable (e.g., strings, numbers, tuples).
Use ...
Random forest and KNN are machine learning algorithms used for classification and regression tasks.
Random forest is an ensemble learning method that constructs multiple decision trees and combines their outputs to make a final prediction.
KNN (k-nearest neighbors) is a non-parametric algorithm that classifies new data points based on the majority class of their k-nearest neighbors in the training set.
Random forest ...
Decision tree is a tree-like model used for classification and regression. OpenCV parameters include image processing and feature detection.
Decision tree is a supervised learning algorithm that recursively splits the data into subsets based on the most significant attribute.
It is used for both classification and regression tasks.
OpenCV parameters include image processing techniques like smoothing, thresholding, an...
I applied via Naukri.com and was interviewed in Apr 2023. There were 3 interview rounds.
Finding index of 2 numbers having total equal to target in a list without nested for loop.
Use dictionary to store the difference between target and each element of list.
Iterate through list and check if element is in dictionary.
Return the indices of the two elements that add up to target.
Random forest and KNN are machine learning algorithms used for classification and regression tasks.
Random forest is an ensemble learning method that constructs multiple decision trees and combines their outputs to make a final prediction.
KNN (k-nearest neighbors) is a non-parametric algorithm that classifies new data points based on the majority class of their k-nearest neighbors in the training set.
Random forest is us...
Python dictionaries are versatile data structures for storing key-value pairs, enabling efficient data retrieval and manipulation.
Dictionaries are created using curly braces: example = {'key': 'value'}
Access values using keys: example['key'] returns 'value'.
Dictionaries are mutable; you can add or remove items: example['new_key'] = 'new_value'.
Keys must be unique and immutable (e.g., strings, numbers, tuples).
Use metho...
To find unique keys in 2 dictionaries.
Create a set of keys for each dictionary
Use set operations to find the unique keys
Return the unique keys
AWS EC2 model deployment involves creating an instance, installing necessary software, and deploying the model.
Create an EC2 instance with the desired specifications
Install necessary software and dependencies on the instance
Upload the model and any required data to the instance
Deploy the model using a web server or API
Monitor the instance and model performance for optimization
Overloading is the ability to define multiple methods with the same name but different parameters.
Overloading allows for more flexibility in method naming and improves code readability.
Examples include defining multiple constructors for a class with different parameter lists or defining a method that can accept different data types as input.
Overloading is resolved at compile-time based on the number and types of argume...
I applied via Naukri.com and was interviewed in Mar 2022. There were 2 interview rounds.
Questions related to Pandas, List, String
Decision tree is a tree-like model used for classification and regression. OpenCV parameters include image processing and feature detection.
Decision tree is a supervised learning algorithm that recursively splits the data into subsets based on the most significant attribute.
It is used for both classification and regression tasks.
OpenCV parameters include image processing techniques like smoothing, thresholding, and mor...
Top trending discussions
Code for parsing a triangle
Use a loop to iterate through each line of the triangle
Split each line into an array of numbers
Store the parsed numbers in a 2D array or a list of lists
The ASCII value is a numerical representation of a character. It includes both capital and small alphabets.
ASCII values range from 65 to 90 for capital letters A to Z.
ASCII values range from 97 to 122 for small letters a to z.
For example, the ASCII value of 'A' is 65 and the ASCII value of 'a' is 97.
I am open to further education to enhance my skills and stay updated with industry trends in data science.
Pursuing a master's degree in data science could deepen my knowledge in advanced analytics.
Online courses in machine learning and AI can help me stay current with emerging technologies.
Attending workshops and conferences can provide networking opportunities and insights from industry leaders.
Certifications in speci...
I appeared for an interview before Jul 2021.
Bagging and boosting are ensemble techniques used to improve the accuracy of machine learning models.
Bagging involves training multiple models on different subsets of the training data and then combining their predictions through voting or averaging.
Boosting involves iteratively training models on the same data, with each subsequent model focusing on the samples that the previous models misclassified.
Bagging reduces va...
I applied via Recruitment Consultant and was interviewed in Jul 2021. There were 3 interview rounds.
Predicting insurance claims using machine learning algorithms.
Fraud detection in insurance claims
Risk assessment for insurance policies
Pricing optimization for insurance products
Customer segmentation for targeted marketing
Predictive maintenance for insurance assets
I applied via Recruitment Consultant and was interviewed in Mar 2021. There were 3 interview rounds.
I applied via Recruitment Consultant and was interviewed in Mar 2021. There was 1 interview round.
I applied via Naukri.com and was interviewed before Jul 2021. There were 3 interview rounds.
Diffie-Hellman algorithm is a key exchange protocol used to securely exchange cryptographic keys over a public channel.
It is based on the concept of discrete logarithm problem.
It involves two parties, Alice and Bob, who generate their own private and public keys.
The public keys are exchanged and used to generate a shared secret key.
The shared secret key is used for encryption and decryption of messages.
It is widely use...
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