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Python Package for ML-Based Heterogeneous Treatment Effects Estimation
EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal of combining state-of-the-art machine learning techniques with econometrics to bring automation to complex causal inference problems. One of the biggest promises of machine learning is to automate decision-making in a multitude of domains. At the core of many data-driven...
Deep learning optimization library: makes distributed training easy
DeepSpeed is an easy-to-use deep learning optimization software suite that enables unprecedented scale and speed for Deep Learning Training and Inference. With DeepSpeed you can:
1. Train/Inference dense or sparse models with billions or trillions of parameters
2. Achieve excellent system throughput and efficiently scale to thousands of GPUs
3. Train/Inference on resource constrained GPU systems
4. Achieve unprecedented low latency and high throughput for inference
5. Achieve extreme...