人工智能對金融世界的改變

The race of tech leaders for AI is so rude and competitive. Things are getting changed day after day by AI. Web development is no exception.

AI的技術領導者競賽是如此粗魯和競爭。 人工智能日新月異。 Web開發也不例外。

Having a website is mandatory for all business niches in the market. And AI will empower web design and development. According to a Statista report, the revenue generation from AI is expected to reach $126 Billion in 2025.

網站是市場上所有業務細分領域的必備條件。 人工智能將支持Web設計和開發。 根據Statista的一份報告，到2025年，來自AI的收入預計將達到1260億美元 。

As a web software engineer, I choose to give you today a brief vision about the top AI and ML frameworks for the web to keep an eye on in 2020 and beyond. This will change the web developer role and in-demand skills in the future.

作為一名網絡軟件工程師，我選擇今天為您簡要介紹一下網絡的頂級AI和ML框架，以便在2020年及以后繼續關注。 將來，這將改變Web開發人員的角色和需求技能。

Ready? Let’s go ?~ ?(?)?

準備？ 出發吧???(?)?

張量流 (Tensorflow)

TensorFlow is a library for machine learning in JavaScript developed by the Google Brain team and introduced in 2015.

TensorFlow是由Google Brain團隊開發并于2015年推出JavaScript機器學習庫。

特點： (Characteristics:)

• Written In: C++, Python and, CUDA

  撰寫： C ++，Python和CUDA

• Platforms: Linux, macOS, Microsoft Windows, and Android.

  平臺： Linux，macOS，Microsoft Windows和Android。

關鍵點： (Key points:)

• Web developers can run existing models in the browser or under Node.js.
  Web開發人員可以在瀏覽器中或在Node.js下運行現有模型。
• Retrain pre-existing Machine Learning models using your data (Transfer Learning)
  使用數據重新訓練已有的機器學習模型(轉移學習)
• Develop ML with flexible and intuitive JavaScript APIs.
  使用靈活直觀JavaScript API開發ML。

阿帕奇·馬豪(Apache Mahout) (Apache Mahout)

Apache Mahout is an open-source machine learning framework developed by Apache Software Foundation in 2008.

Apache Mahout是Apache Software Foundation在2008年開發的開源機器學習框架。

特點： (Characteristics:)

• Written In: Java and Scala

  撰寫： Java和Scala

• Platforms: Apache Hadoop, Apache Spark, Apache Flink, Scala+

  平臺： Apache Hadoop，Apache Spark，Apache Flink，Scala +

關鍵點： (Key points:)

• Improve web application performance by using distributed linear algebra frameworks with mathematically expressive R-Like Scala DSL for distributed algorithms.

  通過將分布式線性代數框架與具有數學表達能力的R-Like Scala DSL用于分布式算法一起使用，可以提高Web應用程序的性能。

• Build scalably supervised (classification) and unsupervised (grouping) machine learning systems in the cloud with Apache Hadoop library.
  使用Apache Hadoop庫在云中構建可擴展的監督(分類)和不受監督(分組)機器學習系統。
• Clustering implementations to discover similarities between items and grouping data thus enhance recommendation systems.
  聚類實現以發現項目和分組數據之間的相似性，從而增強了推薦系統。

Microsoft認知工具包 (Microsoft Cognitive Toolkit)

A free and easy-to-use open-source and deep-learning toolkit. Developed by Microsoft Research and founded in 2016.

一個免費且易于使用的開源和深度學習工具包 。 由Microsoft Research開發，于2016年成立。

特點： (Characteristics:)

• Written In: C++ and Python

  撰寫： C ++和Python

• Platforms: Windows, Linux

  平臺： Windows，Linux

• Model Types: Support feed-forwards DNNs, convolutional and recurrent neural networks

  模型類型：支持前饋DNN，卷積和遞歸神經網絡

關鍵點： (Key points:)

• Efficient for image recognition
  高效的圖像識別
• Efficient for voice recognition
  高效的語音識別
• Efficient for handwriting recognition
  高效的手寫識別
• Used and known by big companies for its speech recognition, predictive analysis, and understanding large unstructured datasets, capabilities.
  被大公司使用并因其語音識別，預測分析以及理解大型非結構化數據集和功能而聞名。

Caffe2 (Caffe2)

Caffe2 is a flexible deep learning framework developed by Berkeley Vision and Learning Center and recently part of PyTorch.

Caffe2是由Berkeley Vision and Learning Center開發的靈活的深度學習框架，并且是PyTorch的一部分。

特點： (Characteristics:)

• Written In: C++ and Python

  撰寫： C ++和Python

• Platforms: Linux, macOS, Windows

  平臺： Linux，macOS，Windows

關鍵點： (Key points:)

• Easy to use and quick.
  易于使用和快速。
• Flexible and high-performance framework for your machine learning product uses.
  適用于您的機器學習產品的靈活而高性能的框架。
• Modular and facilitate fast prototyping of ideas and experiments in deep learning.
  模塊化并促進深度學習中思想和實驗的快速原型制作。

阿帕奇·辛加(Apache Singa) (Apache Singa)

Apache Singa is a scalable and flexible Deep Learning platform developed by Apache Software Foundation and introduced in 2015.

Apache Singa是由Apache Software Foundation開發并于2015年引入的可擴展且靈活的深度學習平臺。

特點： (Characteristics:)

• Written In: C++, Python, Java

  撰寫： C ++，Python，Java

• Platforms: Linux, macOS, Windows

  平臺： Linux，macOS，Windows

關鍵點： (Key points:)

• Scalability: SINGA parallelizes the training and optimizes the communication cost to improve training scalability.

  可擴展性：SINGA 使培訓并行化并優化通信成本，以提高培訓的可擴展性。

• Efficiency: builds a computational graph to optimizes the training speed and memory footprint.

  效率： 建立計算圖以優化訓練速度和內存占用。

• Usability: has a simple software stack and Python interface to improve usability.

  可用性：具有簡單的軟件堆棧和Python界面以提高可用性。

外賣： (Takeouts:)

• There is no doubt that AI is transforming the IT world.
  毫無疑問，人工智能正在改變IT世界。
• It evident too that it will bring a lot of value and power to web development.
  同樣很明顯，它將為Web開發帶來很多價值和力量。
• Stats are showing the big competition around this field.
  統計數據顯示該領域的巨大競爭。
• Tomorrow web developers will be more competitive with AI and ML skills.
  明天的Web開發人員將在AI和ML技能方面更具競爭力。
• Web applications will become smarter with AI.
  借助AI，Web應用程序將變得更加智能。

• According to this article, 84% of businesses say that Artificial Intelligence will enable them to sustain or obtain a competitive advantage.

  根據這篇文章 ，84％的企業表示人工智能將使他們能夠維持或獲得競爭優勢。

• According to this article, 72% of respondents in the technology, media, and telecommunications industry expect AI to have a significant impact on product offerings in the next five years.

  根據本文所述，技術，媒體和電信行業中72％的受訪者預計AI在未來五年內將對產品提供產生重大影響。

Dear reader, thank you for your time. Follow me for more interesting stories about web development and AI \ (???) /

親愛的讀者，謝謝您的寶貴時間。 跟隨我，獲得有關Web開發和AI的更多有趣故事\(???)/

See you soon (ﾉ?ヮ?)ﾉ*:･ﾟ?

很快見(ﾉ?ヮ?)ﾉ *：･ ﾟ?

FAM

FAM

翻譯自: https://levelup.gitconnected.com/ai-revolution-is-changing-the-web-world-fe38e751ede

人工智能對金融世界的改變

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