Showing 5 open source projects for "data visualization, research"

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  • 1
    Scanpy

    Scanpy

    Single-cell analysis in Python

    Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.
    Downloads: 2 This Week
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  • 2
    EconML

    EconML

    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.
    Downloads: 1 This Week
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  • 3
    Causal ML

    Causal ML

    Uplift modeling and causal inference with machine learning algorithms

    Causal ML is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research [1]. It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data. Essentially, it estimates the causal impact of intervention T on outcome Y for users with observed features X, without strong assumptions on the model form. ...
    Downloads: 1 This Week
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  • 4
    LLM Foundry

    LLM Foundry

    LLM training code for MosaicML foundation models

    Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy...
    Downloads: 1 This Week
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  • 5
    Sockeye

    Sockeye

    Sequence-to-sequence framework, focused on Neural Machine Translation

    Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial. If you are interested in collaborating or have any questions, please submit a pull request or issue. You can also send questions...
    Downloads: 0 This Week
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