My solutions to the problems in Fifty Challenging Problems in Probability by Frederick Mosteller

『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)

A curated list of practical financial machine learning tools and applications.

Automatic Functional Differentiation in JAX

Using shadcn-ui components in streamlit

A pedagogical implementation of Autograd

Auto Differentiate from scratch based on Autograd

Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

Best Practices on Recommendation Systems

Python library to build pretty command line user prompts ✨Easy to use multi-select lists, confirmations, free text prompts ...

Panel: The powerful data exploration & web app framework for Python

A community dedicated to supporting tools for technical and scientific communication and interactive computing

High-performance TensorFlow library for quantitative finance.

ARCH models in Python

😎 Curated list of awesome software for numerical analysis and scientific computing

Collection of puzzles in macroeconomics

Template for Python Projects

市場データからインプライド・ボラティリティを計算し，ボラティリティ・スマイルを確認する．

kaityo256/yaml_cv の実行環境

A Hugo theme component to display nice notices

Live streaming radio recoder

Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.

Oryx is a library for probabilistic programming and deep learning built on top of Jax.

Mathematical operations for JAX pytrees

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Julia package for function approximation

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

A curated list of awesome mathematics resources