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machine-learning-library

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Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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rasa

RasaHQ / rasa

Star 13.3k

💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

nlp bot machine-learning natural-language-processing bots botkit chatbot bot-framework nlu spacy mitie chatbots machine-learning-library wit rasa conversational-agents conversational-bots chatbots-framework conversational-ai conversation-driven-development
  • Updated Dec 31, 2021
  • Python

mlpack / mlpack

Star 3.9k
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Remove remaining boost parts with the standard library

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shrit
shrit commented Nov 16, 2021

Hi,

There are still parts of boost library that are used inside mlpack, more specifically in here

  • mlpack/src/mlpack/core/tree/cosine_tree/cosine_tree.hpp boost::heap
  • mlpack/src/mlpack/core/data/load_arff.hpp boost::tokenizer
  • mlpack/tests/main_tests/emst_test.cpp boost::math::iround()
  • mlpack/core/tree/cosine_tree/cosine_tree.cpp boost::m
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help wanted good first issue s: unanswered update dependencies
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RubixML / ML

Sponsor
Star 1.5k

A high-level machine learning and deep learning library for the PHP language.

php data-science machine-learning natural-language-processing algorithm ai deep-learning neural-network analytics clustering cross-validation regression prediction artificial-intelligence classification rubix machine-learning-library feature-vector hidden-layers anomaly-detection classification-trees regression-trees php-ml php-ai php-machine-learning
  • Updated Dec 28, 2021
  • PHP

dreamquark-ai / tabnet

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Open

Helper function for embeddings

Optimox
Optimox commented Dec 13, 2020

Feature request

As requested by some, and as @ekamioka started on this PR #244. It might be interesting to get some helper functions to use embeddings as it's not the simplest concept in deep learning.

What is the expected behavior?
Calling a few helper function to get all the correct parameters before using TabNet

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enhancement good first issue
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