Level Up Your Python for Data Science: Top Interview Questions to Crack the Code! ??
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Level Up Your Python for Data Science: Top Interview Questions to Crack the Code! ??

Ronak Verma Ronak Verma

Ronak Verma

Data Scientist |3X Microsoft certified |2X Databricks certified | 3X IBM certified | 5X DeakinCo. certified | Rajasthan Police Hackathon '24 Finalist | Gen AI | Machine Learning | Deep Learning | Django developer

发布日期: 2024年2月18日
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Want to nail your next data science interview? Mastering Python is key! Here are some essential questions (categorized by difficulty) to guide your preparation:

Beginner Level:

  1. What is Python? Why is it widely used in data science?
  2. Explain the difference between a list and a tuple in Python.
  3. What is the purpose of NumPy in Python?
  4. How do you handle missing or null values in a pandas DataFrame?
  5. What is the difference between loc and iloc in pandas?
  6. Explain the concept of list comprehension in Python.

Intermediate Level:

  1. What is the purpose of the map and apply functions in Python?
  2. How do you handle categorical data in a machine learning pipeline?
  3. Explain the concept of regularization in machine learning.
  4. What is the difference between a shallow copy and a deep copy in Python?
  5. Discuss the differences between supervised and unsupervised learning.
  6. How does the Global Interpreter Lock (GIL) impact multi-threaded Python programs?

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Advanced Level:

  1. Explain the concept of gradient descent in the context of machine learning.
  2. What is the purpose of the init method in a Python class?
  3. Discuss the pros and cons of using ensemble methods in machine learning.
  4. How would you handle imbalanced datasets in a classification problem?
  5. Explain the working of Principal Component Analysis (PCA) and its applications.
  6. What are decorators in Python? Provide an example of how they can be used.

Expert Level:

  1. Discuss the differences between NumPy arrays and Python lists.
  2. Explain the concept of a generator in Python. Provide a use case.
  3. How would you optimize a machine learning model for deployment in a production environment?
  4. Discuss the use of deep learning frameworks like TensorFlow or PyTorch in data science.
  5. Explain the concept of cross-validation and why it is important in machine learning.
  6. Discuss the challenges and strategies for handling big data in a data science project.

?? Ronak verma



Kajal Singh

HR Operations | Implementation of HRIS systems & Employee Onboarding | HR Policies | Exit Interviews

10 个月

Well elaborated. Since data is critical to training an accurate model, if professionals missed an important subset of this data while training the model, unfortunately, they cannot retrain this model by only using the missing data subset. Hence, this effectively implies "changing anything, changes everything", which underlines the interconnected nature of AI systems. This also emphasizes the intricate maintenance process for contemporary AI systems and points out that changes in one aspect necessitate re-evaluating the entire system. This maintenance process, known as MLOps, involves DataOps for data engineering pipelines, ModelOps for machine learning model upkeep, and MLDevOps encompassing software, hardware, and networking management. Each of these sub-processes is crucial for sustained system functionality and requires collaboration among AI professionals, subject matter experts, and business leaders. The next three sections briefly explore each of these sub-processes, underscoring MLOps not only in research and development but also from a business standpoint (due to the substantial time and cost investment that is required during the entire MLOps process) More about this topic: https://lnkd.in/gPjFMgy7

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Naveena yellampalli

"SAP TM Consultant | Supply Chain Management| Actively Seeking Job Opportunities"

11 个月

#crackdsinterview

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Piotr Malicki

NSV Mastermind | Enthusiast AI & ML | Architect Solutions AI & ML | AIOps / MLOps / DataOps | Innovator MLOps & DataOps for Web2 & Web3 Startup | NLP Aficionado | Unlocking the Power of AI for a Brighter Future??

1 年

Impress them with Python skills like a pro! Ready to ace that data science interview? ?? #crackdsinterview

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