Machine Learning and Deep Learning | VincentVan

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https://vincentvannf.github.io/2022/07/31/ML/#15-4-%E5%87%8F%E5%B0%91%E6%98%A0%E5%B0%84%E4%B8%8E%E6%95%B0%E6%8D%AE%E5%B9%B6%E8%A1%8C%EF%BC%88Map-Reduce%EF%BC%89

机器学习，深度学习基础知识。

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Machine Learning is a superset of Deep Learning. It focuses on the development of a computer program that accesses the data and uses it to learn from itself. Deep learning on the other hand create models exactly just like machine learning but it consists of many more levels of algorithms. All these networks of the algorithm are together called the artificial neural network. In much simpler terms, it replicates just like the human brain as all the neural networks are connected in the brain, which exactly is the concept of deep learning. It solves all the complex problems with the help of algorithms and its process.

Machine learning and deep learning differ from each other as follows:

• 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).

• ML use various types of automated algorithms that turn to model functions and predict future action from data.

• DL use neural network that passes data through processing layers to, interpret data features and relations.

• ML algorithms are detected by data analysts to examine specific variables in data sets.

• DL algorithms are largely self-depicted on data analysis once they’re put into production.