PyTorch Training and Certification in Kuala Lumpur, Malaysia

This course provides a comprehensive introduction to PyTorch, a powerful deep learning framework widely used for research and production. Participants will learn the fundamental concepts of tensors, automatic differentiation, neural network construction, and optimization. The course covers deep learning model building, training, and deployment, along with hands-on exercises to develop real-world AI applications using PyTorch.

Introduction to PyTorch and Tensors

• Overview of PyTorch and its ecosystem
• Installing and setting up PyTorch
• Understanding tensors and tensor operations
• Automatic differentiation and computation graphs

Neural Networks and Model Training

• Introduction to PyTorch’s torch.nn module
• Building feedforward neural networks (FNNs)
• Activation functions and loss functions
• Optimizers: SGD, Adam, and other gradient-based methods

Advanced PyTorch and Model Deployment

• Working with PyTorch’s DataLoader and dataset utilities
• Convolutional Neural Networks (CNNs) for image classification
• Recurrent Neural Networks (RNNs) for sequence modeling
• Transfer learning and fine-tuning pre-trained models
• Deploying PyTorch models using TorchScript and ONNX
• Hands-on: Implementing and deploying a PyTorch-based AI model