Week 7

Chapter 7 compares TensorFlow and PyTorch, two well-known deep learning frameworks. Google-developed TensorFlow boasts a bigger ecosystem and is well known for its performance and deployment via tools like TensorFlow Serving and TensorFlow Lite. Facebook-developed PyTorch is increasingly popular in research because of its Pythonic, intuitive API and dynamic computation graphs, which make coding and debugging easier. While TensorFlow has improved ease of use with version 2.0, PyTorch remains the go-to choice for experimentation and learning.

Although they are machine learning tools, they offer insight even for non-technical students in fields like accounting. As data and automation continue to revolutionize the accounting industry, having a general understanding of how machine learning tools work can be helpful. For example, they can help with tasks like fraud detection, financial forecasting, or cost analysis using predictive models.

After graduation, such knowledge can fill the gap between accounting and data science teams. At a corporate finance role or fintech company, familiarity with such frameworks as TensorFlow and PyTorch makes you a viable candidate for a technology-driven field. Even if you don't build models yourself, familiarity with such tools can make you a more flexible and future-ready professional.



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