4. Alternative Methods for Converting Tensors to NumPy Arrays in TensorFlow
   Understanding Tensors and NumPy Arrays:Tensor: A multi-dimensional array in TensorFlow, representing data in a specific format
5. Troubleshooting 400% Higher Error in PyTorch Model Compared to Keras (Adam Optimizer)
   TensorFlow, Keras, PyTorch: These are popular deep learning frameworks used to build and train neural networks. While Keras can run on top of TensorFlow or other backends
6. Crafting Effective Training Pipelines: A Hands-on Guide to PyTorch Training Loops
   In Keras (a high-level deep learning API), fit() provides a convenient way to train a model.It encapsulates common training steps like: Data loading and preprocessing Forward pass (calculating predictions) Loss calculation (evaluating model performance) Backward pass (computing gradients) Optimizer update (adjusting model weights based on gradients)
7. Bridging the Gap: Integrating Matplotlib with TensorBoard for Enhanced Data Exploration
   TensorBoard's Image Dashboard: This built-in feature is designed to visualize image data. While it primarily handles tensors representing images