A deep dive in deep learning ocean with Pytorch & TensorFlow

Course Contents Deep Learning and revolutionized Artificial Intelligence and data science.  Deep Learning teaches computers to process data in a way that is inspired by the human brain.This is complete and comprehensive course on deep learning. This course covers the theory and intuition behind deep learning models and then implementing all the deep learning models both in PyTorch and TensorFlow.Practical Oriented explanations Deep Learning Models with implementation both in PyTorch and TensorFlow.No need of any prerequisites. I will teach you everything from scratch.Job Oriented Structure Sections of the Course· Introduction of the Course· Introduction to Google Colab· Python Crash Course· Data Preprocessing· Regression Analysis· Logistic Regression· Introduction to Neural Networks and Deep Learning· Activation Functions· Loss Functions· Back Propagation· Neural Networks for Regression Analysis· Neural Networks for Classification· Dropout Regularization and Batch Normalization· Optimizers· Adding Custom Loss Function and Custom Layers to Neural Networks· Convolutional Neural Network (CNNs)· One Dimensional CNNs· Setting Early Stopping Criterion in CNNs· Recurrent Neural Network (RNNs)· Long Short-Term Memory (LSTMs) Network· Bidirectional LSTMs· Generative Adversarial Network (GANs)· DCGA Ns· Autoencoders· LSTMs Autoencoders· Variational Autoencoders· Neural Style Transfer· Transformers· Vision Transformer· Time Series Transformers. K-means Clustering. Principle Component Analysis.  Deep Learning Models with implementation both in PyTorch and TensorFlow.