Because of its capacity to handle and learn from massive volumes of data, deep learning—a branch of machine learning within AI—has become a crucial technology for numerous applications. For handling complex data, feature extraction, scalability, and etc, deep learning (DL) is important and widely used. Using R and Python, we will study artificial neural networks and DL in this workshop. We begin by going over the fundamentals and providing an introduction to DL. Following that, we will go over shallow neural networks and build on our previous knowledge of data analysis using convolutional and recurrent neural networks in R and Python, presuming that the audience is familiar with these programmes. Neural network learning using both programmes is essential for those working in statistics and related fields. We also cover topics like hyperparameter tuning, optimization, propagations, and the mathematics behind DL.
