Hi.. I need some urgent assistance. Would you be able to help me today? Require assistance to complete model training for binary classification, image recognition. Required to train an image recognition Convolutional Neural Network (CNN) model that is able to accurately detect images and do exploratory data analysis, displaying in PySpark. Using a human face emotions dataset to train a model to distinguish between happy and sad faces. - Must make use of PySpark for the Exploratory Data Analysis. Do not have to train model using PySpark - Dataset Hyperparameters: * Forced images to be 48x48 * For training using batch sizes of 32 * Training with 8 Epochs * Using a GPU * Using PyTorch not IntensiveLock W.r.t. the convolutional neural network it is basic. Pooling layer The convolutional layer Nothing hardset, flexible at the moment and nothing computationally complex Pyton - 3.9.x Java (JDK) - 8 PySpark - 3.3.2 NumPy - 1.26.4 pandas - 1.5.3 PyArrow - 10.0.1 Variables - set manually in Command Prompt before Spark Dataset: https://www.kaggle.com/datasets/samithsachidanandan/human-face-emotions