PyTorch: Deep Learning and Artificial Intelligence
PyTorch: Deep Learning and Artificial Intelligence - Neural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!
PyTorch is an open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing. It is primarily developed by Facebook’s AI Research lab (FAIR). PyTorch provides two high-level features: tensor computation (like NumPy) with strong acceleration via graphics processing units (GPU) and deep neural networks built on a tape-based autodiff system1.
PyTorch has become one of the most popular deep learning frameworks in recent years due to its ease of use and flexibility. It has been used in many research projects and production systems1.
If you want to learn more about PyTorch, you can check out this course on Udemy called “PyTorch: Deep Learning and Artificial Intelligence” 1. It covers topics such as tensors, neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, generative adversarial networks (GANs), and more.
What you'll learn
- Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
- Predict Stock Returns
- Time Series Forecasting
- Computer Vision
- How to build a Deep Reinforcement Learning Stock Trading Bot
- GANs (Generative Adversarial Networks)
- Recommender Systems
- Image Recognition
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Natural Language Processing (NLP) with Deep Learning
- Demonstrate Moore's Law using Code
- Transfer Learning to create state-of-the-art image classifiers
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