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Machine Learning Guideline
This article aims to prepare machine learning database in order to show all machine learning titles in one view. This article will be updated when a new article related with machine learning title is published. This guideline can be called as a table of content of this project.
There are millions of resources on machine learning on the internet. These resources explain machine learning topics in detail, supporting with examples. Personally, even if I fully understand it, I cannot put it into practice unless I examine the subject with a omnisciently(god’s view), not just for machine learning but in all fields of study. That’s also the reason of why I prefer the books.
This article aims to compile all machine learning related topics and make them accessible in one article. In this way, while machine learning is solving the problem, all suitable solutions for that problem can be viewed from a single window and more positive results can be obtained. Topics that are forgotten or wanted to be reviewed can be read again with just one click. In addition, details that are overlooked for the data science and model evaluation section can shed light on the projects.
The contents of this article are the result of a combination of the books I have studied, internet resources and the courses I took at the university. This article will be updated as new titles are added. With its dynamic structure, this article will never be completed, but it will not stop competing with itself. The subjects to be examined in the first place as short term goals are as in the image. After examining all of these topics, model evaluation, data science, data manipulation, libraries, pipelines, deep learning, machine learning & deep learning projects and more will be added. By the way, these titles can also be expanded. This dynamic article will be updated regularly.
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