### Q1: What is the primary purpose of TensorFlow within the AI/ML lifecycle?  
### Q2: How does Scikit-learn facilitate traditional machine learning tasks?  
### Q3: What are some advanced features of TensorFlow that make it suitable for deep learning tasks?  
### Q4: In what scenarios would Scikit-learn be a more efficient choice than TensorFlow for predictive modeling?  
### Q5: How can understanding project requirements impact the selection of AI/ML tools?  
### Q6: What considerations should be taken into account regarding team expertise when choosing between TensorFlow and Scikit-learn?  
### Q7: How can effective communication skills enhance the collaboration of team members when selecting AI/ML tools for a project?  
### Q8: What strategies can be employed to clearly present the benefits of TensorFlow and Scikit-learn to stakeholders?  
### Q9: How can you ensure that your team is aligned on the criteria for selecting AI/ML tools during project discussions?