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机器学习(ML)是计算机系统为了有效地执行特定任务,不使用明确的指令,而依赖模式和推理使用的算法和统计模型的科学研究。它被视为人工智能的一个子集。机器学习算法构建一个基于样本数据的数学模型,称为“训练数据”,以便在没有明确编程来执行任务的情况下进行预测或决策。[1][2]机器学习算法用于各种应用,例如电子邮件过滤和计算机视觉,在这些应用中,开发用于执行任务的特定指令的算法是不可行的。机器学习与计算统计学密切相关,计算统计学侧重于使用计算机进行预测。算法优化的研究为机器学习领域提供了方法、理论和应用领域。数据挖掘是机器学习中的一个研究领域,侧重于探索性数据分析到无监督学习。[3][4]在跨业务问题的应用中,机器学习也被称为预测分析。
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机器学习+实验.zip (2000个子文件)
handWriteClassify.py 2KB
annTest.py 2KB
dataAnalysis.py 2KB
imgToMatrix.py 1KB
demo.py 923B
NpIoTest.py 610B
fenbu.py 443B
__init__.py 0B
__init__.py 0B
__init__.py 0B
__init__.py 0B
knnDataSet.txt 25KB
5_71.txt 1KB
5_41.txt 1KB
9_30.txt 1KB
3_47.txt 1KB
5_15.txt 1KB
9_40.txt 1KB
0_24.txt 1KB
9_78.txt 1KB
9_51.txt 1KB
2_54.txt 1KB
0_6.txt 1KB
1_76.txt 1KB
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5_3.txt 1KB
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