💻 Software & Environment Setup
AI & Machine Learning in Healthcare
The computational toolchain and environment used throughout Deep Learning for Histopathology Image Analysis.
Deep learning workshopDeep learning training for researchersImage analysis training for researchersHistopathology training for researchersConvolutional neural networks (cnns) workshopConvolutional neural networks (cnns) training for researchers
# Recommended conda environmentconda create -n dstc_env python=3.11 -yconda activate dstc_envpip install torch torchvision scikit-learn monai pydicomPyTorch / TensorFlow
Deep-learning model training
Deep-learning model training
MONAI
Medical-imaging deep-learning framework
Medical-imaging deep-learning framework
scikit-learn
Classical ML, evaluation & pipelines
Classical ML, evaluation & pipelines
Weights & Biases
Experiment tracking & reproducibility
Experiment tracking & reproducibility
Supported OS: Linux (Ubuntu 22.04+), macOS, or Windows via WSL2.
Hardware: 16 GB RAM minimum; a CUDA GPU helps for deep-learning modules.
Earn government-registered certification in Deep Learning for Histopathology Image Analysis
e-Certificate and e-Marksheet issued on successful completion.
