# 機器學習以及程式語言(Traditional Chinese)

DevFeed: [機器學習以及程式語言(Traditional Chinese)](<https://devfeed.tech/articles/traditional-chinese-46272.md>)

Original publisher: [Read original article](<https://julialang.org/blog/2017/12/ml-pl-zh_tw/index.html>)

Author: By Mike Innes (JuliaHub); David Barber (UCL); Tim Besard (UGent); James Bradbury (Salesforce Research); Valentin Churavy (MIT); Simon Danisch (MIT); Alan Edelman (MIT); Stefan Karpinski (JuliaHub); Jo

Published: 2017-12-25T00:00:00Z

Content type: opinion

Language: zh-tw

Sources: [JuliaLang - The Julia programming language](<https://devfeed.tech/sources/julialang-the-julia-programming-language.md>)

Topics: [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [Tensorflow](<https://devfeed.tech/topics/tensorflow.md>), [Python](<https://devfeed.tech/topics/python.md>), [Graphs](<https://devfeed.tech/topics/graphs.md>), [GPU](<https://devfeed.tech/topics/gpu.md>)

Tags: [gpu](<https://devfeed.tech/tags/gpu.md>), [graphs](<https://devfeed.tech/tags/graphs.md>), [lazy](<https://devfeed.tech/tags/lazy.md>), [metaprogramming](<https://devfeed.tech/tags/metaprogramming.md>), [ml](<https://devfeed.tech/tags/ml.md>), [overhead](<https://devfeed.tech/tags/overhead.md>), [python](<https://devfeed.tech/tags/python.md>), [tensorflow](<https://devfeed.tech/tags/tensorflow.md>)

## AI overview

This essay examines whether machine learning needs a purpose-built programming language. It explains how systems such as TensorFlow use Python APIs to construct graph-based languages and discusses the trade-offs among metaprogramming, runtime flexibility, performance, parallelism, automatic differentiation, and deployment to small devices. It also compares approaches including Chainer and MXNet Gluon.

## Source excerpt

機器學習以及程式語言(Traditional Chinese) | > 任何足夠複雜的機器學習系統都包含一個特別設置、不符規範、充滿 bug 又緩慢實作的程式語言半成品。^greenspun ...