FLAML is a lightweight Python library from Microsoft for automating machine learning and AI operations. It performs model selection and hyperparameter optimization under resource constraints, including tuning foundation model inference hyperparameters. It requires Python 3.10 or later, is installable via pip, and can be used as a scikit-learn style estimator.
Gensim is a free open-source Python library for topic modelling and semantic NLP. It trains large-scale semantic models, represents text as semantic vectors and finds semantically related documents. The site describes streaming of arbitrarily large corpora, platform independence, and pretrained models and corpora published by the community.
Fiber is a Python-based distributed computing library for modern computer clusters. It provides the same API as Python's standard multiprocessing library, uses Nanomsg for communication, and allows dynamic allocation of CPU, memory, and GPU resources. Installation uses pip install fiber.
spaCy is a free open-source library for Natural Language Processing in Python. It features named entity recognition, part-of-speech tagging, dependency parsing and word vectors, supports over 75 languages and provides 84 trained pipelines for 25 languages.
Text Mining with R: A Tidy Approach is a website for a guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools. It is written by Julia Silge and David Robinson and licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.
An article by Cavin on Deep Markets discussing machine-generated content and creativity. It describes technology as leverage over creation: writing, the printing press, the internet, digital tools and machine learning. It also covers synthetic text from large language models such as OpenAI's GPT-3, published in summer 2020.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
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Gensim is a free open-source Python library for topic modelling and semantic NLP. It trains large-scale semantic models, represents text as semantic vectors and finds semantically related documents. The site describes streaming of arbitrarily large corpora, platform independence, and pretrained models and corpora published by the community.
Fiber is a Python-based distributed computing library for modern computer clusters. It provides the same API as Python's standard multiprocessing library, uses Nanomsg for communication, and allows dynamic allocation of CPU, memory, and GPU resources. Installation uses pip install fiber.
spaCy is a free open-source library for Natural Language Processing in Python. It features named entity recognition, part-of-speech tagging, dependency parsing and word vectors, supports over 75 languages and provides 84 trained pipelines for 25 languages.
Text Mining with R: A Tidy Approach is a website for a guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools. It is written by Julia Silge and David Robinson and licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.
An article by Cavin on Deep Markets discussing machine-generated content and creativity. It describes technology as leverage over creation: writing, the printing press, the internet, digital tools and machine learning. It also covers synthetic text from large language models such as OpenAI's GPT-3, published in summer 2020.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
