AIMonk Interview Questions and Answers

Q1. What is accuracy in ml
Ans. 
Accuracy in machine learning measures how often the model makes correct predictions.
• Accuracy is the ratio of correctly predicted instances to the total instances in the dataset.

• It is a common evaluation metric for classification models.

• Accuracy can be calculated using the formula: (TP + TN) / (TP + TN + FP + FN), where TP = True Positives, TN = True Negatives, FP = False Positives, FN = False Negatives.

• For example, if ...read more
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Q2. What is recall in ml
Ans. 
Recall is a metric in machine learning that measures the ability of a model to find all relevant cases within a dataset.
• Recall is calculated as the ratio of true positive cases to the sum of true positive and false negative cases.

• It is also known as sensitivity or true positive rate.

• A high recall value indicates that the model is good at identifying all relevant cases, even if it means more false positives.

• For example,...read more
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We were asked to created an application on local system using yolo for object detection and use container as well.

Q1. Decorators in python
Ans. 
Decorators in Python are functions that modify the behavior of other functions.
• Decorators are defined using the @decorator_name syntax before a function definition.

• They can be used to add functionality to existing functions without modifying their code.

• Common use cases include logging, timing, and access control.

• Example: @staticmethod decorator in Python makes a method static.
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Q2. Dropout, batch normalization
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Q3. Ensemble methods
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Q4. Tensorflow basic questions were asked. About custom model and custom dataset.
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Q1. Basics in python
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Q2. Basic and advanced concepts in ML
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Assignment given to you over mail.

Python basic coding test

Q1. Technical indepth machine learning theory question related to project done in your past company
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