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Preferred Networks
- Tokyo, Japan
- in/shotarosano
- https://www.kaggle.com/shotaro
Highlights
- Pro
Stars
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
unofficial Python implementation to demonstrate PLaMo-100B
Elasticsearch integration into LangChain
Atomistic simulation hands on tutorial on Matlantis
FizzBuzz Enterprise Edition is a no-nonsense implementation of FizzBuzz made by serious businessmen for serious business purposes.
⚡️ AllenNLP plugin for adding subcommands to use Optuna, making hyperparameter optimization easy
Examples for https://github.com/optuna/optuna
HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
PFRL: a PyTorch-based deep reinforcement learning library
Synchronize your working directory efficiently to a remote place without committing the changes.
Real-time Web Dashboard for Optuna.
A Rust implementation of fANOVA (functional analysis of variance)
Flexible Feature Engineering & Exploration Library using GPUs and Optuna.
Supplementary components to accelerate research and development in PyTorch
Python library for CMA Evolution Strategy.
A shell-friendly hyperparameter search tool inspired by Optuna
Machine learning tasks which are used with data pipeline library "luigi" and its wrapper "gokart".
A flexible framework of neural networks for deep learning
A hyperparameter optimization framework, inspired by Optuna.
4th Place Solution for Kaggle Competition: Quora Insincere Questions Classification