The fundamental step to work on a Machine Learning project is to state well the problem you want to solve. Usually, the problem definition comes from a business or a domain like marketing, finance, medicine, engineering, and others. Thus, we must state the problem in terms of the business or the domain and then map it to a typical Machine Learning task.
(more…)Category: Lists
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Small Machine Learning Projects
This page contains a list of links to small machine learning projects, which you can use as examples or to bootstrap a more significant projects.
- Create your first machine learning model in 5 minutes with Google Colab
- Introduction to Linear Regression With One Variable
- How to scale attributes with normalization and standartization
We will update this page as we publish new projects. Each blog post describes the project and contain links to Github repositories or Kaggle kernels.
Updated in 2020-03-19.
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40 Resources to Completely Master Markov Decision Processes
The Markov Decision Process is the formal description of the Reinforcement Learning problem. It includes concepts like states, actions, rewards, and how an agent makes decisions based on a given policy. So, what Reinforcement Learning algorithms do is to find optimal solutions to Markov Decision Processes.
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