Answer Posted / Pankaj Rana

TensorFlow has several potential drawbacks:n1. Steep Learning Curve: TensorFlow's API can be complex and difficult for beginners to grasp.n2. Resource Intensive: Training deep learning models in TensorFlow requires significant computational resources, which can make it challenging for users with limited hardware.n3. Verbose Code: TensorFlow code can be verbose and difficult to read, especially when compared to other libraries like PyTorch.n4. Not Ideal for Real-Time Applications: Due to its complex architecture, TensorFlow may not be suitable for real-time applications that require quick processing speed.n5. Lack of Community Support for Certain Platforms: While TensorFlow has a large community, support for some platforms can be limited.

What are the apis outside tensorflow project?

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