机器学习和深度学习的区别

机器学习：机器学习是人工智能 (AI) 的一个子集，它为系统提供了从经验中学习和改进的能力，而无需编程到该级别。机器学习使用数据来训练和找到准确的结果。机器学习侧重于开发访问数据并使用数据进行自我学习的计算机程序。

深度学习：深度学习是机器学习的一个子集，其中人工神经网络、循环神经网络相互关联。算法的创建与机器学习完全一样，但它包含更多级别的算法。该算法的所有这些网络统称为人工神经网络。简单来说，它就像人脑一样复制，因为所有的神经网络都连接在大脑中，这正是深度学习的概念。它借助算法及其过程解决所有复杂问题。

下表列出了机器学习和深度学习之间的差异：

S.No.	Machine Learning	Deep Learning
1.	Machine Learning is a superset of Deep Learning	Deep Learning is a subset of Machine Learning
2.	The data represented in Machine Learning is quite different as compared to Deep Learning as it uses structured data	The data representation is used in Deep Learning is quite different as it uses neural networks(ANN).
3.	Machine Learning is an evolution of AI	Deep Learning is an evolution to Machine Learning. Basically it is how deep is the machine learning.
4.	Machine learning consists of thousands of data points.	Big Data: Millions of data points.
5.	Outputs: Numerical Value, like classification of score	Anything from numerical values to free-form elements, such as free text and sound.
6.	Uses various types of automated algorithms that turn to model functions and predict future action from data.	Uses neural network that passes data through processing layers to the interpret data features and relations.
7.	Algorithms are detected by data analysts to examine specific variables in data sets.	Algorithms are largely self-depicted on data analysis once they’re put into production.
8.	Machine Learning is highly used to stay in the competition and learn new things.	Deep Learning solves complex machine learning issues.