machine-learning-course-notes

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machine-learning-course-notes

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A collection of notes and codes of my Msc course on Machine Learning

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# machine-learning-course-notes
machine-learning-course-notes

## cheatsheet
-----
* [Jupyter notebook](cheatsheet/jupyter.pdf)
* [Numpy](cheatsheet/numpy.pdf)
* [Scikit learn](cheatsheet/scikitlearn.pdf)

***Resources*** 
------

[100 days of machine learning](https://github.com/Avik-Jain/100-Days-Of-ML-Code)

[Deep learning](https://github.com/shohans-galaxy/awesome-deep-learning)

[হাতেকলমে মেশিন লার্নিং](https://rakibul-hassan.gitbook.io/mlbook-titanic/)

[wtfpython](https://github.com/shohans-galaxy/wtfpython)

[machine learning with python](https://www.datacamp.com/tracks/machine-learning-with-python)

[python-for-programmers](https://www.educative.io/track/python-for-programmers)

[become-ml-engineer](https://www.educative.io/track/become-ml-engineer)

[maths fo machine learning](https://medium.com/s/story/essential-math-for-data-science-why-and-how-e88271367fbd)

**[machine-learning-course](https://github.com/machinelearningmindset/machine-learning-course)**

**[Tweet Size ML Implementation](https://github.com/eriklindernoren/NapkinML)**

***Dataset download free***

1. [https://catalog.data.gov/dataset](https://catalog.data.gov/dataset)
2. [BuzzFeed News Data](https://github.com/BuzzFeedNews/everything)
3. [Fivethirtyeight](https://github.com/fivethirtyeight/data)
4. [Kaggle](https://www.kaggle.com/datasets)
5. [Data world](https://data.world/)

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