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머신러닝 · GitHub

모델 학습, 평가, 추론 프레임워크를 찾고 커뮤니티의 관심도를 비교하세요.

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SGC

Tiiiger

851스타

official implementation for the paper "Simplifying Graph Convolutional Networks"

l4casadi

Tim-Salzmann

597스타

Use PyTorch Models with CasADi for data-driven optimization or learning-based optimal control. Supports Acados.

35스타
foundationforecast preview

FoundationForecast: the Python API for Time Series Foundation Models ✨. It supports forecasting, cross-validation, anomaly detection, and exogenous variables for models such as AWS Chronos, Google TimesFM, Mistral Timestral, H2O TimeH2O, Nixtla TimeGPT, etc., under the same API.

  • 📐 Conformal prediction intervals. Use ConformalIntervals to calibrate any model's level / quantiles from point-forecast errors, with optional finite-sample correction; see the guide and example notebook.
  • 📈 Exogenous variables (covariates). Pass known-future features with X_df on forecast() (and exog columns in df for cross_validation()). Native support on Chronos-2, TimesFM-3, TimeGPT, T0, TimeH2O, TiRex-2, and Timestral; see Exogenous variables and the example notebook.
머신러닝PythonApache-2.0GitHub

ENet

TimoSaemann

597스타

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

991스타
tensorflow2-generative-models preview

Implementations of a number of generative models in Tensorflow 2. GAN, VAE, Seq2Seq, VAEGAN, GAIA, Spectrogram Inversion. Everything is self contained in a jupyter notebook for easy export to colab.

머신러닝Jupyter NotebookGitHub
270스타

Set of vectorizers that extract keyphrases with part-of-speech patterns from a collection of text documents and convert them into a document-keyphrase matrix.

머신러닝PythonBSD-3-ClauseGitHub

courseware

tinyMLx

222스타
courseware preview

In this repository you will find TinyML course syllabi, assignments/labs, code walkthroughs, links to student projects, and lecture videos (where applicable).

tiramisu

Tiramisu-Compiler

964스타

A polyhedral compiler for expressing fast and portable data parallel algorithms

LSTM-FCN

titu1994

806스타

Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification

-chanlun

tomcat123a

570스타

文件 笔和线段的一种划分.py,只需要把k线high,low数据输入,就能自动实现笔,线段,中枢,买卖点,走势类型的划分了。可以把sh.csv 作为输入文件。个人简历见.pdf。时间的力量。有人说择时很困难,有人说选股很容易,有人说统计套利需要的IT配套设施很重要。还有人说系统有不可测原理。众说纷纭。分布式的系统,当你的影响可以被忽略,你才能实现,Jiang主席所谓之,闷声发大财。第一周,大盘跌了1%,挣钱了一万,挣了5%。 #股票 #股市 #缠论 https://v.kuaishou.com/bFEl6M Copy this message and open 【Kwai】to view!