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The Intel® Deep Learning Framework
The main features of intel/idlf are: Data Science Tooling.
Projects with overlapping indexed features include: albumentations-team/albumentations — Albumentations is a computer vision image augmentation library designed to increase training data diversity for deep… alteryx/featuretools — Featuretools is an automated feature engineering library and data transformation framework written in Python. It… asavinov/lambdo — Feature engineering and machine learning: together at last! astrazeneca/chemicalx — A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022). astrazeneca/rexmex — A general purpose recommender metrics library for fair evaluation. adrotog/pandasgui — A GUI for Pandas DataFrames.
Albumentations is a computer vision image augmentation library designed to increase training data diversity for deep learning models. It provides a toolset for applying geometric and color transformations to images and annotations, including a specialized collection of 3D operations for volumetric data used in medical and scientific imaging. The library functions as an image mask and bounding box transformer, automatically updating masks, bounding boxes, and keypoints when images undergo geometric changes. This ensures that spatial alterations remain synchronized across images and their assoc
Featuretools is an automated feature engineering library and data transformation framework written in Python. It automatically generates machine learning feature vectors from multi-table datasets by applying synthesis patterns to relational and timestamped data. The system functions as a distributed feature synthesis engine, allowing the process of creating feature vectors to scale across multiple cores or clusters to handle large-scale datasets. The library supports the synthesis of multi-table datasets, time series feature generation, and the creation of custom machine learning primitives
