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machine-learning-algorithms

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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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TheAlgorithms / C-Plus-Plus

Star 17.3k

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

search computer-science machine-learning algorithm algorithms cpp machine-learning-algorithms mathematics sort data-structures educational algorithm-competitions interview-questions hacktoberfest algorithms-implemented interview-preparation artificial-intelligence-algorithms instructor-materials
  • Updated Dec 25, 2021
  • C++

TheAlgorithms / C

Star 12k

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.

c search computer-science education machine-learning algorithms datastructures machine-learning-algorithms mathematics interview sort learn-to-code data-structures educational algorithm-competitions interview-questions algorithm-challenges hacktoberfest community-driven
  • Updated Dec 28, 2021
  • C
nni

microsoft / nni

Star 10.7k

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

python data-science machine-learning deep-learning neural-network tensorflow machine-learning-algorithms pytorch distributed feature-extraction hyperparameter-optimization feature-engineering nas bayesian-optimization automl automated-machine-learning model-compression neural-architecture-search deep-neural-network
  • Updated Dec 29, 2021
  • Python
Learn-Data-Science-For-Free

therealsreehari / Learn-Data-Science-For-Free

Star 4.8k

This repositary is a combination of different resources lying scattered all over the internet. The reason for making such an repositary is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Data Science. For Constant Updates Follow me in Twitter.

data-science machine-learning natural-language-processing computer-vision machine-learning-algorithms artificial-intelligence neural-networks deeplearning datascienceproject
  • Updated Apr 2, 2021

rapidsai / cudf

Star 4.4k
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[FEA] Consider removing default value from `stream` parameter in detail functions.

3
nvdbaranec
nvdbaranec commented Dec 7, 2021

Based on @karthikeyann's work on this PR rapidsai/cudf#9767 I'm wondering if it makes sense to consider removing the defaults for the stream parameters in various detail functions. It is pretty surprising how often these are getting missed.

The most common case seems to be in factory functions and various ::create functions. Maybe just do it for those?

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feature request good first issue libcudf tech debt
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cleanlab / cleanlab

Star 2.6k

The standard package for machine learning with noisy labels, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.

machine-learning machine-learning-algorithms weak-supervision semi-supervised-learning unsupervised-learning data-cleaning clean-data learning-with-confident-examples noisy-data data-centric confident-learning latent-estimation robust-machine-learning learning-with-noisy-labels
  • Updated Dec 27, 2021
  • Python

rapidsai / cuml

Star 2.5k
Open

[DOC] Add docstrings to functions, classes, and methods in api_context_managers.py

wphicks
wphicks commented Feb 8, 2021

Report needed documentation

Report needed documentation
While the estimator guide offers a great breakdown of how to use many of the tools in api_context_managers.py, it would be helpful to have information right in the docstring during development to more easily understand what is actually going on in each of the provided functions/classes/methods. This is particularly important for

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good first issue ? - Needs Triage doc
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stellargraph / stellargraph

Star 2.2k
Open

Consolidate example graphs in unit tests

2
adocherty
adocherty commented Nov 27, 2019

Description

Currently our unit tests are disorganized and each test creates example StellarGraph graphs in different or similar ways with no sharing of this code.

This issue is to improve the unit tests by making functions to create example graphs available to all unit tests by, for example, making them pytest fixtures at the top level of the tests (see https://docs.pytest.org/en/latest/

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good first issue sg-library

krishnakumarsekar / awesome-quantum-machine-learning

Star 1.9k

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

machine-learning awesome ai qml tensorflow quantum machine-learning-algorithms artificial-intelligence quantum-computing artificial-neural-networks awesome-list fcm kmeans ant-colony-optimization quantum-programming-language hmm-model qubits knn-classification quantum-ai
  • Updated Oct 26, 2020
  • HTML

tslearn-team / tslearn

Star 1.9k
Open

KMeans question

8
ssimontacchi
ssimontacchi commented Jun 20, 2020

Hi, Thanks for the awesome library!

So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).

I conceptually

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bug good first issue
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