机器学习：机器学习是人工智能 (AI) 的使用，它使框架能够自然地吸收和改进，而无需明确修改。机器学习以 PC 程序的进步为中心，这些程序可以获取信息并使用它来为自己学习。
学习之路从感知或信息开始，例如模型、直接洞察力或指导，以在信息中搜索设计，然后根据我们提供的模型确定更好的选择。关键是允许计算机在没有人工干预或帮助的情况下自然适应，并根据需要改变活动。
统计：统计是一种数值调查，它利用对给定的测试信息或真实考试安排的模型、描绘和大纲进行评估。统计学考虑了从信息中收集、审计、剖析和推断的方法。
统计是一个术语，总而言之，审查员用来描述数据集的周期。如果信息收集依赖于更多人群的例子，那么审查员可以从根本上依赖于来自该例子的事实结果来创建对民众的理解。统计包括社交场合和评估信息的方式，然后将数据汇总为数字结构。
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Machine Learning |
Statistics |
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Machine Learning is a lot of steps or rules taken care of by the user where the machine comprehends and train without anyone else. |
Statistics is a numerical idea in finding the pattern from the information. |
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It makes the most accurate prediction possible and then foresee future events or arrange a current material. |
It interfaces the relationship between the variables and finds out the connection between the information points. |
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Inputs and Outputs are labels and features. |
Inputs and Outputs are Data points. |
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It consists of Mathematics and Algorithms. |
It consists of only Mathematical and Statistical Information. |
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It is mainly used in the hypothesis or prediction. |
It is mainly used to find a correlation between the data points, univariate, multivariable, etc. |
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It concerned in the field of Data Science and Artificial Intelligence with concepts like predominant algorithms and neural networks. |
It concerned in the field of Data Analytics and Artificial Intelligence with concepts like probabilities and derivatives. |
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Keywords: Decision Tree, Neural Networks, Logistic Regression, Support Vector Machine, etc. |
Keywords: Covariance, Univariate, Estimators, etc. |
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Types: Supervised, Unsupervised, and Reinforcement Learning. |
Types: Regression, Classification, and Forecasting Continuous Variable. |
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Applications: Weather forecasting, Stock Market Prediction, etc. |
Applications: Statistics description techniques, finding patterns in the data, outliers in the data, etc. |