The purpose of this project is to provide a comprehensive and yet simple course in Machine Learning using Python. You can access to the full documentation with the following links:
Machine Learning
, as a tool for Artificial Intelligence
, is one of the most widely adopted
scientific fields. A considerable amount of literature has been published on Machine Learning.
The purpose of this project is to provide the most important aspects of Machine Learning
by presenting a
series of simple and yet comprehensive tutorials using Python
. In this project, we built our
tutorials using many different well-known Machine Learning frameworks such as Scikit-learn
. In this project you will learn:
- What is the definition of Machine Learning?
- When it started and what is the trending evolution?
- What are the Machine Learning categories and subcategories?
- What are the mostly used Machine Learning algorithms and how to implement them?
Title | Document |
---|---|
An Introduction to Machine Learning | Overview |
Title | Code | Document |
---|---|---|
Linear Regression | Python | Tutorial |
Overfitting / Underfitting | Python | Tutorial |
Regularization | Python | Tutorial |
Cross-Validation | Python | Tutorial |
Title | Code | Document |
---|---|---|
Decision Trees | Python | Tutorial |
K-Nearest Neighbors | Python | Tutorial |
Naive Bayes | Python | Tutorial |
Logistic Regression | Python | Tutorial |
Support Vector Machines | Python | Tutorial |
Title | Code | Document |
---|---|---|
Clustering | Python | Tutorial |
Principal Components Analysis | Python | Tutorial |
Title | Code | Document |
---|---|---|
Neural Networks Overview | Python | Tutorial |
Convolutional Neural Networks | Python | Tutorial |
Autoencoders | Python | Tutorial |
Recurrent Neural Networks | Python | IPython |
Please consider the following criterions in order to help us in a better way:
- The pull request is mainly expected to be a link suggestion.
- Please make sure your suggested resources are not obsolete or broken.
- Ensure any install or build dependencies are removed before the end of the layer when doing a build and creating a pull request.
- Add comments with details of changes to the interface, this includes new environment variables, exposed ports, useful file locations and container parameters.
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We are looking forward to your kind feedback. Please help us to improve this open source project and make our work better. For contribution, please create a pull request and we will investigate it promptly. Once again, we appreciate your kind feedback and support.
Creator: Machine Learning Mindset [Blog, GitHub, Twitter]
Supervisor: Amirsina Torfi [GitHub, Personal Website, Linkedin ]
Developers: Brendan Sherman*, James E Hopkins* [Linkedin], Zac Smith [Linkedin]
*: equally contributed