PyTorch courses
Learn how to use PyTorch, a popular machine learning framework, to build and train AI models. These courses cover the fundamentals of deep learning, working with tensors, and developing neural networks using Python. You'll also explore how PyTorch is used in natural language processing (NLP) and other AI applications.Related topics:
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PyTorch courses (10)
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- Learn how to use PyTorch to build, train, and test artificial neural networks in this course.
- Intermediate.3 hours
- Learn to build neural networks and deep neural networks for tabular data, text, and images with PyTorch.
- Includes 8 Courses
- With Certificate
- Intermediate.18 hours
- Build AI classification models with PyTorch using binary and multi-label techniques.
- With Certificate
- Beginner Friendly.3 hours
- Learn how to use Python to build image classification models using CNNs and vision transformers in this PyTorch tutorial.
- With Certificate
- Intermediate.5 hours
- Learn how to use Python to build text generation models based on neural networks like RNNs and LSTMs in this PyTorch tutorial.
- With Certificate
- Intermediate.3 hours
- Learn how to use PyTorch in Python to build text classification models using neural networks and fine-tuning transformer models.
- With Certificate
- Intermediate.4 hours
- Learn neural network architectures with PyTorch to build deep learning models for image, text, and sequential data tasks.
- With Certificate
- Intermediate.2 hours
- Learn how to build a Generative Pre-trained Transformer (GPT) from scratch using PyTorch.
- With Certificate
- Intermediate.2 hours
- Dive into unsupervised learning with autoencoders. Train models to reconstruct high-dimensional images and denoise corrupted images using PyTorch in colab.
- Intermediate.2 hours
- Dive into AI with Generative Adversarial Networks (GANs). Learn to use PyTorch for model creation and training, and Deep Convolutional GANs for image optimization.
- Intermediate.2 hours
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Frequently asked questions about PyTorch courses
PyTorch is an open-source machine learning framework used for building and training deep learning models. It is widely used in AI, natural language processing (NLP), and neural network research.
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