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HTML
CSS
Python
PHP
MySQL
Linux
Shobha
The best way to predict the future is to invent it
What are the common pitfalls when working with real-time data in analytics?
RELATED INTERVIEW QUESTIONS
What is the role of Bayesian methods in data analytics, and how do they compare to frequentist approaches?
What are the differences between LSTM and GRU networks in deep learning?
Can you explain the no free lunch theorem in machine learning and its implications on choosing algorithms for different types of problems?
What are the limitations of using random forests for classification tasks?
How do you handle imbalanced datasets in classification problems, and what techniques do you use to improve the model’s performance?
Explain the role of backpropagation in training neural networks.
What is stratified sampling, and when should it be used in machine learning?
How would you assess the performance of a machine learning model over time?
What is the importance of data preprocessing in machine learning, and what steps are involved?
How do you ensure that a machine learning model is interpretable for non-technical stakeholders?
What is dimensionality reduction, and how does PCA (Principal Component Analysis) help?
What are the advantages and limitations of using SQL vs NoSQL for large-scale analytics?
How do you use data augmentation to improve a deep learning model’s performance?
How do you perform feature importance analysis for model interpretability?
What are the challenges of data visualization, and how do you overcome them?
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