Determined the importance of AI Ethics such as Responsibility, Interpretability, Fairness, and Misuse. Created a project with six other team members on the CIFAR-10 Image Classification using Deep Learning and Self Driving Cars. Created an accurate pipeline to recognize certain objects using ML. Performed EDA, learning that the dictionary assigns values for each class in the dataset. Used traditional neural network algorithm as the Baseline Model with 3 fully connected layers with ReLu activation function. 

For the Advanced Model, we used Transfer Learning, VGG16, Resnet34 / Resnet50, DenseNet121, Data Augmentation (Flipping, Rotations, relighting, reshaping etc.) and improved CNN model using Conv2D, Batch Normalization layers, Padding, Strides, Dropout, Pooling, More Dense Layers, Epochs, Batches, validation / test split.We even utilized Learning rate, Kernel_initializer / Kernel_regularizer, more data augmentation, K-fold cross validation (multiple validation sets) to increase the accuracy and reduce Mean Squared Error.