A deep dive in deep learning ocean with Pytorch & TensorFlow

Course ContentsDeep 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 Tensor flow. Practical Oriented explanations Deep Learning Models with implementation both in Pytorch and Tensor Flow. No need of any prerequisites.

I will teach you everything from scratch. Job Oriented StructureSections 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 (CNN)· One Dimensional CNN· Setting Early Stopping Criterion in CNN· Recurrent Neural Network (RNN)· Long Short-Term Memory (LSTM) Network· Bidirectional LSTM· Generative Adversarial Network (GAN)· DCGANs· Autoencoders· LSTM 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 Tensor Flow.