Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep

Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep lear

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classif

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks. Key FeaturesTrain your own models for effec