Machine learning consists of three parts: supervised learning, unsupervised learning, and reinforcement learning.
The three learning algorithms focus on teaching a machine to learn from its mistakes, to improve, and to improve. Is knowledge of data structures and algorithms absolutely necessary?
Not exactly! No one expects you to know how to use linked lists, tree search, or recursion to build predictive models. However, you need to understand arrays and vectors.
Predictive modeling in R and Python is mostly based on packages and libraries. These packages and libraries are hardcoded so that a user does not need to do any serious coding other than calling these libraries and performing calculations on them.
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Do Machine Learning Engineers Need To Know Data Structures And Algorithms?
Short StoryMachine learning consists of three parts: supervised learning, unsupervised learning, and reinforcement learning. The three learning algorithms focus on teaching a machine to learn from its mistakes, to improve, and to improve. Is knowledge of data...
