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Python 3 | K-TechLaboゼミ用å¦ç¿’ノート
Python3入門ã®ãŸã‚ã®PDFテã‚ストをé…布ã—ã¦ã„ã¾ã™ï¼Ž 「Python3入門ã€ã€€ï¼ˆãƒŸãƒ©ãƒ¼ã‚µã‚¤ãƒˆï¼‘）（ミラーサイト２） 公開ã—ã¦ã„るテã‚ストã«é–¢ã™ã‚‹è³ªå•ã‚„メッセージãŠå¾…ã¡ã—ã¦ã„ã¾ã™ï¼Ž 「Python3 ライブラリブック〠（ミラーサイト１）（ミラーサイト２） ã€Python3入門ã®ç›®æ¬¡ã€‘ 1　ã¯ã˜ã‚ã«ã€€â€”　1 1.1　Pythonã§ã§ãã‚‹ã“ã¨ã€€â€”　1 1.2　本書ã®å†…容　—　1 1.3　本書ã®èªã¿æ–¹ã€€â€”　1 1.4　処ç†ç³»ã®å°Žå…¥ï¼ˆã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ï¼‰ã¨èµ·å‹•ã®æ–¹æ³•ã€€â€”　2 1.4.1　Python処ç†ç³»ã®ãƒ‡ã‚£ã‚¹ãƒˆãƒªãƒ“ューション（é…布形態）　—　2 1.4.2　Python処ç†ç³»ã®èµ·å‹•ã€€â€”　2 1.4.3　対話モード　—　3 1.4.3.1　ヒストリ　—　3 1.4.3.2　直å‰ã®å€¤ã€€â€”　3 1.5　本書ã§å–り扱ã†GUIライブラリ　—　4 1.6　表記ã«é–¢ã™ã‚‹æ³¨æ„äº‹é …ã€€â€”ã€€4 1.7　Python
NumPyã®æ´å²ã¨Pythonã®ä¸¦è¡Œå‡¦ç†
Python has become a standard for interactive scientific research. NumPy arrays can represent multi-dimensional data and support common operations. Parallel processing can speed up tasks using multiprocessing or multithreading. Executors allow running functions concurrently by mapping tasks to threads or processes.Read less
GitHub - ddbourgin/numpy-ml: Machine learning, in numpy
Click to expand! Gaussian mixture model EM training Hidden Markov model Viterbi decoding Likelihood computation MLE parameter estimation via Baum-Welch/forward-backward algorithm Latent Dirichlet allocation (topic model) Standard model with MLE parameter estimation via variational EM Smoothed model with MAP parameter estimation via MCMC Neural networks Layers / Layer-wise ops Add Flatten Multiply
Python in Excel alternative: Open. Self-hosted. No limits.
The Open, Enterprise-Ready Alternative to Python in Excel Latest xlwings release: v0.33.4 xlwings is a modern and privacy-first spreadsheet programming package with a beautiful API. Privacy-first: Python can be installed locally or on on your self-hosted server for easy deployment. Cross-platform: Supports Excel on Windows, macOS, and on the Web. xlwings Reader and xlwings Server run everywhere wh
rawpy · PyPI
Tip: You can dynamically query supported features by inspecting the rawpy.flags dictionary. Note on GPL demosaic packs: The GPL2 and GPL3 demosaic packs are not included as rawpy is licensed under the MIT license which is incompatible with GPL. Installation from source on Linux/macOS For macOS, LibRaw is built as part of the rawpy build (see external/). For Linux, you need to install the LibRaw li
Pythonã§è‹±æ–‡é¡žä¼¼è¨˜äº‹æ¤œç´¢ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ : TF-IDF, Cosine類似度 - Qiita
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[GUIDE] How to install numpy+scipy in Maya Windows 64 bit?
Welcome to Autodesk’s Maya Forums. Share your knowledge, ask questions, and explore popular Maya SDK topics.
numpy/dropping-python2.7-proposal.rst at master · numpy/numpy · GitHub
Plan for dropping Python 2.7 support The Python core team plans to stop supporting Python 2 in 2020. The NumPy project has supported both Python 2 and Python 3 in parallel since 2010, and has found that supporting Python 2 is an increasing burden on our limited resources; thus, we plan to eventually drop Python 2 support as well. Now that we're entering the final years of community-supported Pytho
Pythonã®æ•°å€¤è¨ˆç®—ライブラリ NumPy入門
Scientific Computing Tools For Python — Numpy NumPy 㯠Pythonプãƒã‚°ãƒ©ãƒŸãƒ³ã‚°è¨€èªžã®æ‹¡å¼µãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã§ã‚ã‚Šã€å¤§è¦æ¨¡ãªå¤šæ¬¡å…ƒé…列や行列ã®ã‚µãƒãƒ¼ãƒˆã€ã“れらをæ“作ã™ã‚‹ãŸã‚ã®å¤§è¦æ¨¡ãªé«˜æ°´æº–ã®æ•°å¦é–¢æ•°ãƒ©ã‚¤ãƒ–ラリをæä¾›ã™ã‚‹ã€‚(via Wikipedia) ã“ã‚Œã¾ã§çŸ¥è˜ãŒã‚ã„ã¾ã„ã ã£ãŸNumPyã«ã¤ã„ã¦ã€ã‚‚ã†ä¸€åº¦ãŠã•ã‚‰ã„ã—ãŸã„ã¨æ€ã„ã¾ã™ã€‚NumPyã¯SciPyã¨ä½µã›ã¦ç§‘å¦æŠ€è¡“計算ã§ã‚ˆã利用ã•ã‚Œã¦ã„ã¾ã™ã€‚ã¾ãŸã€é«˜é€Ÿã«è¡Œåˆ—演算ãŒã§ãã‚‹ã®ã§OpenCV(コンピュータビジョンライブラリ)ã§ã‚‚NumPyを利用ã—ãŸPythonインタフェースãŒæä¾›ã•ã‚Œã‚‹ã‚ˆã†ã«ãªã‚Šã¾ã—ãŸã€‚ OpenCVã®Pythonãƒã‚¤ãƒ³ãƒ‡ã‚£ãƒ³ã‚°ã«ã¤ã„ã¦ã¯åŽ»å¹´ã®ã‚¨ãƒ³ãƒˆãƒªãƒ¼ã§ã‚‚å–り上ã’ã¦ã„ã¾ã™ã®ã§å‚考ã¾ã§ã«ã€‚ * ã•ãらVPSã«OpenCVをインストールã—ã¦Pythonã‹ã‚‰ä½¿ã† [2017/04/2
Numba: High-Performance Python with CUDA Acceleration | NVIDIA Technical Blog
Looking for more? Check out the hands-on DLI training course: Fundamentals of Accelerated Computing with CUDA Python [Note, this post was originally published September 19, 2013. It was updated on September 19, 2017.] Python is a high-productivity dynamic programming language that is widely used in science, engineering, and data analytics applications. There are a number of factors influencing the
CuPy
NumPy/SciPy-compatible Array Library for GPU-accelerated Computing with Python High performance with GPU CuPy is an open-source array library for GPU-accelerated computing with Python. CuPy utilizes CUDA Toolkit libraries including cuBLAS, cuRAND, cuSOLVER, cuSPARSE, cuFFT, cuDNN and NCCL to make full use of the GPU architecture. The figure shows CuPy speedup over NumPy. Most operations perform we
線形二次レギュレータ(Linear-Quadratic Regulator:LQR)ã®æ¦‚è¦ã¨Pythonサンプルコード - MyEnigma
ã¯ã˜ã‚ã¦ã®ç¾ä»£åˆ¶å¾¡ç†è«– (KSç†å·¥å¦å°‚門書)posted with カエレãƒä½è—¤ 和也,下本 陽一,熊澤 典良 講談社 2012-09-07 Amazonã§æŽ¢ã™æ¥½å¤©å¸‚å ´ã§æŽ¢ã™Yahooショッピングã§æŽ¢ã™ 目次 目次 ã¯ã˜ã‚ã« LQRã®æ¦‚è¦ Pythonã«ã‚ˆã‚‹LQRã®åˆ¶å¾¡ã‚·ãƒŸãƒ¥ãƒ¬ãƒ¼ã‚·ãƒ§ãƒ³ Githubリãƒã‚¸ãƒˆãƒª LQRã®ãƒ‘ラメータã®ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°æ–¹æ³• ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°æ–¹æ³•ï¼‘ ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°æ–¹æ³•ï¼’ ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°æ–¹æ³•3 å‚考資料 MyEnigma Supporters ã¯ã˜ã‚㫠最近ã€ãƒãƒœãƒƒãƒˆã®åˆ¶å¾¡ã‚„経路生æˆã®å‹‰å¼·ã‚’ã—ã¦ã„ã‚‹ã®ã§ã™ãŒã€ ã—ã°ã—ã°å‡ºã¦ãる技術ã¨ã—ã¦ã€ 線形二次レギュレータ(Linear-Quadratic Regulator:LQR)ãŒã‚ã‚Šã¾ã™ã€‚ 今回ã¯ã“ã®LQRã®æ¦‚è¦ã¨LQRã«ã‚ˆã‚‹ ç°¡å˜ãªPython制御シミュレーションコードを紹介ã—ãŸã„ã¨æ€ã„ã¾ã™ã€‚ LQRã®æ¦‚è¦ LQRã¯æœ€é©åˆ¶å¾¡ã¨å‘¼ã°
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GitHub - microsoft/vscode-gather: Gather for the Python Extension
GitHub - JohannesBuchner/imagehash: A Python Perceptual Image Hashing Module
GitHub - joblib/joblib: Computing with Python functions.
GitHub - numba/numba: NumPy aware dynamic Python compiler using LLVM
GitHub - iamtrask/Grokking-Deep-Learning: this repository accompanies the book "Grokking Deep Learning"
GitHub - google/burst-denoising
https://qiita.com/_Me_takuya/items/6b60de80b065a94fd81d
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