TensorBoard is a visualization tool provided by TensorFlow that allows for monitoring of various metrics during model training, such as loss values, accuracy, and visualization of model structure and computation graph.
Matplotlib is a Python plotting library that can be used to create various types of charts such as line plots, bar plots, scatter plots, etc. In TensorFlow, matplotlib can be used to visualize changes in metrics during model training and model prediction results.
Seaborn is a Python data visualization library based on matplotlib, offering a higher-level interface to make plotting simpler and more visually appealing. It can be used to create various statistical charts such as box plots and heatmaps.
The Python Imaging Library (PIL) is a graphics processing library for Python, which can be used to read, process, and display images. In TensorFlow, PIL can be used to visualize the image data of model inputs and outputs.
OpenCV is an open-source computer vision library that offers a wide range of image processing and computer vision algorithms. It can be used in TensorFlow for handling and displaying image data, as well as for visualizing image data.
