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1.
What is TensorFlow and who developed it?
Answer:
TensorFlow Fundamentals
- 2.
What are the main features of TensorFlow?
Answer: - 3.
Can you explain the concept of a computation graph in TensorFlow?
Answer: - 4.
What are Tensors in TensorFlow?
Answer: - 5.
How does TensorFlow differ from other Machine Learning libraries?
Answer: - 6.
What types of devices does TensorFlow support for computation?
Answer: - 7.
What is a Session in TensorFlow? Explain its role.
Answer: - 8.
What is the difference between TensorFlow 1.x and TensorFlow 2.x?
Answer: - 9.
How does TensorFlow handle automatic differentiation?
Answer: - 10.
What is a Placeholder in TensorFlow, and how is it used?
Answer: - 11.
Could you explain the concept of TensorFlow Lite and where it’s used?
Answer: - 12.
Define a Variable in TensorFlow and its importance.
Answer: - 13.
What are the different data types supported by TensorFlow?
Answer:
Building and Training Models
- 14.
How do you build a neural network in TensorFlow?
Answer: - 15.
Explain the process of compiling a model in TensorFlow.
Answer: - 16.
Describe how TensorFlow optimizers work and name a few common ones.
Answer: - 17.
How do you perform batch processing in TensorFlow?
Answer: - 18.
What is the role of loss functions in TensorFlow, and can you name some?
Answer: - 19.
How do you implement a custom layer in TensorFlow?
Answer: - 20.
What are the differences between sequential and functional APIs in TensorFlow?
Answer: - 21.
How does TensorFlow support regularization to prevent overfitting?
Answer: - 22.
Explain the concept of saving and restoring a model in TensorFlow.
Answer: - 23.
How do you use callbacks in TensorFlow?
Answer: - 24.
What strategies does TensorFlow use to handle overfitting during training?
Answer:
Advanced TensorFlow Features
- 25.
How does TensorFlow integrate with Keras?
Answer: - 26.
Explain the concept of eager execution in TensorFlow.
Answer: - 27.
Describe the role of tf.data in TensorFlow.
Answer: - 28.
How do you use TensorFlow Transformers for sequence modeling?
Answer: - 29.
What is TensorFlow Distribution Strategies and when would you use it?
Answer: - 30.
Can you explain TensorFlow Extended (TFX) and its main components?
Answer: - 31.
Discuss how TensorFlow can be used for reinforcement learning.
Answer: - 32.
What is TensorFlow Serving and how does it facilitate model deployment?
Answer: - 33.
How does one use TensorFlow’s Estimator API?
Answer:
TensorFlow Performance and Optimization
- 34.
How do you approach optimizing TensorFlow model performance?
Answer: - 35.
What techniques are used in TensorFlow for graph optimizations?
Answer: - 36.
How do you perform memory optimization in TensorFlow?
Answer: - 37.
Explain the concept of quantization in TensorFlow and when it might be used.
Answer: - 38.
Discuss how to use mixed-precision training in TensorFlow.
Answer: - 39.
How does TensorFlow support multi-GPU or distributed training?
Answer: - 40.
What are some best practices for writing efficient TensorFlow code?
Answer:
TensorFlow in Practice and Real-world Applications
- 41.
How do you handle image data in TensorFlow?
Answer: - 42.
Describe the process of text preprocessing in TensorFlow.
Answer: - 43.
Explain how you would approach time-series forecasting with TensorFlow.
Answer: - 44.
What support does TensorFlow offer for transfer learning?
Answer: - 45.
How is TensorFlow deployed in mobile or edge devices?
Answer: - 46.
Can you give an example of how TensorFlow is used in healthcare?
Answer:
TensorFlow Coding Challenges
- 47.
Write a TensorFlow code to create two Tensors and perform element-wise multiplication.
Answer: - 48.
Implement logistic regression using TensorFlow.
Answer: - 49.
Build a simple convolutional neural network in TensorFlow for image classification.
Answer: - 50.
Write a TensorFlow script to normalize the features of a dataset.
Answer: - 51.
Create a recurrent neural network in TensorFlow to process sequential data.
Answer: - 52.
Write a Python function using TensorFlow to compute the gradient of a given function.
Answer: - 53.
Develop a code to save and load a trained TensorFlow model.
Answer: - 54.
Implement a custom training loop in TensorFlow for a basic neural network.
Answer: - 55.
Code a TensorFlow program that uses dataset shuffling, repetition, and batching.
Answer: - 56.
Write a TensorFlow function for data augmentation on an image dataset.
Answer:
TensorFlow Debugging and Troubleshooting
- 57.
How would you go about debugging a TensorFlow model that isn’t learning?
Answer: - 58.
Discuss common errors encountered in TensorFlow and how to resolve them.
Answer: - 59.
How does TensorFlow’s tf.debugging package assist in debugging?
Answer: - 60.
What steps would you take to investigate and fix a shape mismatch error in TensorFlow?
Answer: - 61.
How can the TensorBoard tool be used to debug TensorFlow programs?
Answer:
TensorFlow Advanced Techniques and Current Trends
- 62.
Discuss how GradientTape works in TensorFlow.
Answer: - 63.
How would you implement attention mechanisms in TensorFlow?
Answer: - 64.
Explain the concept of graph mode versus eager mode in TensorFlow.
Answer: - 65.
How is TensorFlow utilized in Natural Language Processing (NLP)?
Answer: - 66.
What are some of the latest features or additions to TensorFlow that are currently gaining traction?
Answer:
TensorFlow Case Studies and Scenario-Based Questions
- 67.
How would you apply TensorFlow to predict stock market trends?
Answer: - 68.
Explain what steps you would take to develop a chatbot using TensorFlow.
Answer: - 69.
Describe how you would use TensorFlow in an autonomous vehicle perception system.
Answer: - 70.
Present an approach for real-time object detection using TensorFlow.
Answer:
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