### Q1: What is the primary advantage of using TensorFlow for AI development in finance, particularly for large-scale projects?  
### Q2: How does the dynamic computation graph of PyTorch enhance the experimentation process for financial model development?  
### Q3: In what scenarios would you prefer to use TensorFlow's Keras API over PyTorch for building neural networks in financial applications?  
### Q4: How can Tableau help in visualizing customer trends in financial products effectively?  
### Q5: What are the key benefits of integrating Power BI with other Microsoft products for financial data analysis?  
### Q6: Describe a situation where Google Data Studio could be more beneficial than Tableau or Power BI for a finance team.  
### Q7: How can Jupyter Notebooks facilitate better communication of model choices to non-technical stakeholders in a finance project?  
### Q8: What are the advantages of using Google Colab for running AI models compared to local setups?  
### Q9: How does incorporating version control tools like GitHub enhance collaboration in AI projects within the finance sector?