y-okt

y-okt's Stars

• TheAlphamerc/flutter_twitter_clone

  Fully functional Twitter clone built in flutter framework using Firebase realtime database and storage

  Language:Dart3.9k1.1k

• JasonShin/sqlx-ts

  node.js compile-time SQL validations & type generations

  Language:Rust1846

• darbyluv2code/spring-and-hibernate-for-beginners

  Source code for the course: Spring and Hibernate for Beginners

  Language:Java803788

• tatsy/normalizing-flows-pytorch

  PyTorch implementations of normalizing flow and its variants.

  Language:Python748

• jwasham/coding-interview-university

  A complete computer science study plan to become a software engineer.

  306k76.8k

• AxelThevenot/Python_Benchmark_Test_Optimization_Function_Single_Objective

  Language:Python8129

• OptMist-Tokyo/DAEPreprocessingToolbox

  MATLAB toolbox for preprocessing of differential-algebraic equations (DAEs)

  Language:MATLAB5

• ZiyueWang25/Kaggle_G2Net

  G2Net Competition

  Language:Jupyter Notebook127

• py-why/EconML

  ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

  Language:Jupyter Notebook3.8k714

• pfnet-research/deep-table

  Language:Python787

• NadeemWard/pytorch_simple_policy_gradients

  Reimplementation of simple policy gradient algorithms such as REINFORCE and Actor-Critic methods.

  Language:Python122

• DEAP/deap

  Distributed Evolutionary Algorithms in Python

  Language:Python5.8k1.1k

• mangye16/Unsupervised_Embedding_Learning

  Code for Unsupervised Embedding Learning via Invariant and Spreading Instance Feature

  Language:Python20845

• karolzak/ipyplot

  IPyPlot is a small python package offering fast and efficient plotting of images inside Python Notebooks. It's using IPython with HTML for faster, richer and more interactive way of displaying big numbers of images.

  Language:Python41441

• Bjarten/early-stopping-pytorch

  Early stopping for PyTorch

  Language:Jupyter Notebook1.2k293

• mercari/ml-system-design-pattern

  System design patterns for machine learning

  2.3k239

• lime-robot/dsb2019

  https://www.kaggle.com/c/data-science-bowl-2019

  Language:Python6623

• lopuhin/kaggle-imet-2019

  Language:Python9124

• supikiti/hydra-mlflow-optuna-sample

  Language:Python341

• optuna/optuna-dashboard

  Real-time Web Dashboard for Optuna.

  Language:TypeScript52186

• optuna/kurobako

  A black-box optimization benchmark tool

  Language:Rust8311

• c-bata/github-actions-kurobako

  GitHub Action to generate kurobako report and comment it to the pull request.

  Language:Python4

• CyberAgentAILab/cmaes

  Python library for CMA Evolution Strategy.

  Language:Python36963

• fkubota/kaggle-Cornell-Birdcall-Identification

  Cornell Birdcall Identification コンペのリポジトリ

  Language:Jupyter Notebook3718

• oxfordcontrol/TRS.jl

  Solving the Trust Region Subproblem as an Eigenproblem in Julia

  Language:Julia226

• fkubota/Carrier-Owl

  arxiv--> DeepL --> Slack/LINE

  Language:Python328359

• TheAlgorithms/Python

  All Algorithms implemented in Python

  Language:Python194k45.6k

• MTrajK/coding-problems

  Solutions for various coding/algorithmic problems and many useful resources for learning algorithms and data structures

  Language:Python3.3k613

• zhiwehu/Python-programming-exercises

  100+ Python challenging programming exercises

  26.8k6.8k

• rasbt/python_reference

  Useful functions, tutorials, and other Python-related things

  Language:Jupyter Notebook3.8k936