摘要
由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于人工智能的新报告。根据NewsRx编辑在马来西亚雪兰莪的新闻报道，研究表明，"肉类是人类生长和发展所必需的必要氨基酸的来源，肉类可以来自故意或经济地（广告）出售给消费者的死亡、活的、清真或非清真动物物种。"新闻记者从Putra Ma Laysia大学的研究中获得了一句话：“伊斯兰教法禁止穆斯林食用猪肉。由于近年来掺假者的活动，消费者知道他们在吃什么。过去，清真食品的认证采用了几种方法，但这种方法存在许多缺点，如缺乏灵活性，摘要:机器学习(ML)是一种从给定数据中开发和应用算法,在不需要显式编程的情况下做出预测或决策的概念。与传统方法相比,该方法具有快速、灵活、可扩展、自动化、成本低等优点。高准确度和敏感性。在肉类认证中使用的一些ML方法已经被证明在肉类认证中具有很高的准确率，而其他方法没有证据表明没有W的清真肉类认证。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting out of Selangor, Malaysia, by NewsRx editors, research stated, “Meat is a source of essential amino acids tha t are necessary for human growth and development, meat can come from dead, alive , Halal, or non-Halal animal species which are intentionally or economically (ad ulteration) sold to consumers.” The news journalists obtained a quote from the research from University Putra Ma laysia: “Sharia has prohibited the consumption of pork by Muslims. Because of th e activities of adulterators in recent times, consumers are aware of what they e at. In the past, several methods were employed for the authentication of Halal m eat, but numerous drawbacks are attached to this method such as lack of flexibil ity, limited application, time,consumption and low level of accuracy and sensiti vity. Machine Learning (ML) is the concept of learning through the development a nd application of algorithms from given data and making predictions or decisions without being explicitly programmed. The techniques compared with traditional m ethods in Halal meat authentication are fast, flexible, scaled, automated, less expensive, high accuracy and sensitivity. Some of the ML approaches used in Hala l meat authentication have proven a high percentage of accuracy in meat authenti city while other approaches show no evidence of Halal meat authentication for no w.”
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