Skater

[wtm_mlop_cats] Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system often needed for real world use-cases(** we are actively working towards to enabling faithful interpretability for all forms models). It is an open source python library designed to demystify the learned […]

SHAPash  – Shapash is a Python library that provides several types of visualization that display explicit labels that everyone can understand.

[wtm_mlop_cats] Shapash is a Python library which aims to make machine learning interpretable and understandable by everyone. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can understand their models easily and share their results. End users can understand the decision proposed by a model using a summary […]

SHAP 

[wtm_mlop_cats] SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions (see papers for details and citations). Features A model says a bank shouldn’t loan someone money, […]

SAGE

[wtm_mlop_cats] Sage is an open source project and completely free to use. However, the amount of effort needed to maintain and develop new features and products within the Roots ecosystem is not sustainable without proper financial backing. Sage is a productivity-driven WordPress starter theme with a modern development workflow. Features Harness the power of Laravel […]

responsibly 

[wtm_mlop_cats] Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems. Responsibly is developed for practitioners and researchers in mind, but also for learners. Therefore, it is compatible with data science and machine learning tools of trade in Python, such as Numpy, Pandas, and especially scikit-learn. The primary goal is to be one-shop-stop […]

rationale

[wtm_mlop_cats] Rationale is inspired by RamdaJS. It is a collection of helper utility functions that are absent in the OCaml/ReasonML standard library. Note that not all of Ramda was ported over, as many of Ramda’s utilities are making up for deficits in Javascript, which Reason doesn’t have. Furthermore, many of the functions that operate on […]

pyBreakDown 

[wtm_mlop_cats] Break Down method is moved to the dalex Python package which is actively maintained. If you will experience any problem with pyBreakDown please consider the dalex implementation at https://dalex.drwhy.ai/python/api/. Official website Link Tutorial and documentation Click here to view See more MLOps tools and solutions

NETRON  

[wtm_mlop_cats] Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn, MNN, PaddlePaddle, Core ML, MXNet, RKNN, MindSpore Lite, TNN, Barracuda, Tengine, TensorFlow.js, Caffe2 and UFF. Netron has experimental support for PyTorch, TensorFlow, TorchScript, OpenVINO, Torch, Vitis AI, Arm NN, BigDL, Chainer, CNTK, […]

mljar-supervised

[wtm_mlop_cats] The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist 😎. It abstracts the common way to preprocess the data, construct the machine learning models, and perform hyper-parameters tuning to find the best model 🏆. It is no black-box as […]

MindsDB  

[wtm_mlop_cats] MindsDB enables advanced predictive capabilities directly in your Database. This puts sophisticated machine learning techniques into the hands of anyone who knows SQL (data analysts, developers and business intelligence users) without the need for a new tool or significant training. Features Prototype AutoML. With MindsDB built-in Automated Machine Learning you can quickly generate the […]