The course Getting Started with Deep Learning is an introduction Deep Learning, its history, and its various applications such as Computer Vision, Natural Language Processing, etc.
-
Image Classification with the MNIST Dataset : "Hello World" of deep learning, training a deep learning model to correctly classify hand-written digits.
-
Image Classification of an American Sign Language Dataset : Perform data preparation, model creation, and model training using a different dataset: images of hands making letters in American Sign Language.
-
Convolutional Neural Networks : Introduction to a popular kind of model called a convolutional neural network that is especially good for reading images and classifying them.
-
Data Augmentation : Learn how to avoid overfitting using Data Augmentation.
-
Deploying Your Model : Expose new images to our model and detect the correct letters of the sign language alphabet.
-
Pre-Trained Models : Explore available models such as VGG.
-
Transfer Learning : Use Transfer Learning to create a doggy door that only lets in a particular dog.
-
Generate Headlines : Use Recurrent Neural Networks to generate new headlines.
-
Assessment : Train a new model that is able to recognize fresh and rotten fruite using some combination of transfer learning, data augmentation, and fine tuning.