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Monitoring School Meal Quality - 1
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Module 1
Project Setup & PyTorch Fundamentals
1
Setting Up Your Python Environment and Key Libraries
Set up a Python environment with Conda or venv and install key libraries (PyTorch, Hugging Face, OpenCV, GeoPandas).
2
"PyTorch and CUDA Setup for GPU Verification"
Install PyTorch with CUDA support and write a script to verify GPU availability.
3
PyTorch Tensor Fundamentals
Create and manipulate PyTorch tensors, performing essential operations like indexing, reshaping, and arithmetic.
4
Building Your First Neural Network with PyTorch
Define a simple neural network using `torch.nn.Module` and understand its basic structure.
5
Tensor and Model Device Placement with `.to(device)`
Move tensors and models between CPU and GPU using `.to(device)` for accelerated computation.
6
Efficient Data Loading with PyTorch
Use `torch.utils.data.Dataset` and `DataLoader` to create an efficient, batched data loading pipeline.
7
PyTorch Training Loop: A Complete Walkthrough
Implement a complete training loop in PyTorch: forward pass, loss computation, backpropagation, and parameter update.
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Data Acquisition & Exploratory Analysis