Pinned Repositories
100knocks-preprocess_ForColab-AzureNotebook
データサイエンス100本ノック（構造化データ加工編）For Azure_Notebook/Google_Colabo
AI_Quest_PBL01
alife_book_src
「作って動かすALife - 実装を通した人工生命モデル理論入門」サンプルコード
automatestuff-ja
https://www.oreilly.co.jp/books/9784873117782/
backtesting.py
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
book-mlearn-gyomu
すぐに使える！業務で実践できる！Pythonによる AI・機械学習・深層学習アプリのつくり方
TRF
依頼書のAI解析ツール（チェックマーク・手書き文字）
TRF_text_OCR_for_Win
TRF_text_recognition
kmtk49's Repositories
kmtk49/100knocks-preprocess_ForColab-AzureNotebook
データサイエンス100本ノック（構造化データ加工編）For Azure_Notebook/Google_Colabo
kmtk49/AI_Quest_PBL01
kmtk49/alife_book_src
「作って動かすALife - 実装を通した人工生命モデル理論入門」サンプルコード
kmtk49/backtesting.py
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
kmtk49/COVID19
kmtk49/data-science-from-scratch
code for Data Science From Scratch book
kmtk49/deep-learning-from-scratch-2
『ゼロから作る Deep Learning ❷』(O'Reilly Japan, 2018)
kmtk49/discordpy-startup
Herokuでdiscord.pyを始めるテンプレート
kmtk49/dl-in-a-sec
2019年5月発刊『図解速習DEEP LEARNING』（シーアンドアール研究所）のサポートサイトです。
kmtk49/example-scripts
The official example scripts for the Numerai Data Science Tournament
kmtk49/handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
kmtk49/introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
kmtk49/ipython-books.github.io
IPython books website, by Cyrille Rossant
kmtk49/JR
kmtk49/kagglebook
kmtk49/LINE
kmtk49/machine-learning-with-python-cookbook
kmtk49/MiningSocial
kmtk49/nomeroff-net
Nomeroff Net. Automatic numberplate recognition system.
kmtk49/numerai
kmtk49/practical-statistics-for-data-scientists
Code repository for O'Reilly book
kmtk49/Practical-Statistics-for-Data-Scientists-with-MATLAB
This repository provides MATLAB code for the computation described in the book "Statistics for Data Scientists: 50 Essential Concepts." Original R code and data can be found here. https://github.com/andrewgbruce/statistics-for-data-scientists
kmtk49/ProbSpace
kmtk49/pycaret
An open-source, low-code machine learning library in Python
kmtk49/Quants01
kmtk49/Quants02
kmtk49/stable-baselines
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
kmtk49/statistics-for-data-scientists
Code and data associated with the book "Statistics for Data Scientists: 50 Essential Concepts"
kmtk49/StudyAI
report for rabbit challenge 2022#1
kmtk49/yfinance