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TensorFlow machine learning skill specialized for physics applications including neural network potentials and surrogate models
Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum har...
Implement computer vision tasks including image classification, object detection, segmentation, and pose estimation using PyTorch and TensorFlow
Design and architect neural networks with various architectures including CNNs, RNNs, Transformers, and attention mechanisms using PyTorch and TensorFlow
TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias ...
NVIDIA TensorRT — deep learning inference optimizer. FP16/INT8/INT4 quantization, kernel auto-tuning, layer fusion, and dynamic shapes. Max throughput on NVIDIA GPUs for production inference.
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