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Assign tasks based on past performance by analyzing employee's strengths and weaknesses.
Analyze employee's past performance data
Identify their strengths and weaknesses
Assign tasks that align with their strengths
Provide training or support for areas of weakness
Regularly review and adjust task assignments based on performance
Consider employee preferences and career goals
Assuming the blog covers popular sports, the number of viewers can range from a few thousand to millions depending on the quality of content and marketing strategies.
Consider the popularity of the sports covered in the blog
Evaluate the quality of content and frequency of updates
Assess the marketing strategies used to promote the blog
Look at the engagement level of the blog's social media accounts
Take into account the c...
A thief operating in shopping can earn anywhere from a few thousand to millions of dollars per year depending on their tactics and location.
The thief's location and the type of stores they target will greatly impact their earnings
Factors such as the thief's level of experience, skill, and risk-taking behavior will also play a role in their earnings
Some thieves may work alone while others may operate in organized groups...
Understanding car passing probabilities over time helps in traffic analysis and planning.
Probability can be calculated using the formula: P = (number of successful outcomes) / (total outcomes).
If a car passes every 10 minutes on average, in one hour (60 minutes), you expect 6 cars.
For a subset time, adjust the expected number of cars based on the time interval.
Example: In 15 minutes, if 6 cars pass in 60 minutes, expec...
To open the number lock on the bag, you need to try combinations of three numbers, ensuring that at least two of them are correct.
Start by trying the combinations of the first two numbers with each of the remaining six numbers.
If none of these combinations work, move on to the next pair of numbers and repeat the process.
Continue this pattern until you find a combination that opens the lock.
I applied via Recruitment Consultant and was interviewed in Jun 2021. There were 5 interview rounds.
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 ...
I applied via LinkedIn and was interviewed in Nov 2024. There were 2 interview rounds.
Aptitude was quite easy with simple python questions
Asked basic questions on numpy and pandas
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