Machine Learning Notes

ml.md

Time series data

1. https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/
2. http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html
3. https://machinelearningmastery.com/time-series-forecasting-methods-in-python-cheat-sheet/
4. https://www.analyticsvidhya.com/blog/2018/02/time-series-forecasting-methods/
5. https://www.youtube.com/watch?v=e8Yw4alG16Q
6. https://medium.com/@josemarcialportilla/using-python-and-auto-arima-to-forecast-seasonal-time-series-90877adff03c
7. https://www.digitalocean.com/community/tutorials/a-guide-to-time-series-forecasting-with-arima-in-python-3
8. https://www.sciencedirect.com/science/article/pii/S0925231217309864
9. http://publications.lib.chalmers.se/records/fulltext/242944/242944.pdf

Neural Networks/Deep Learning

1. https://www.youtube.com/watch?v=aircAruvnKk
2. https://www.youtube.com/watch?v=b99UVkWzYTQ&list=PLjJh1vlSEYgvGod9wWiydumYl8hOXixNu

Data pre-processing

1. https://app.pluralsight.com/library/courses/pandas-data-wrangling-machine-learning-engineers/table-of-contents
2. https://developers.google.com/machine-learning/guides/text-classification/step-3
3. https://app.pluralsight.com/library/courses/python-scikit-learn-building-machine-learning-models/table-of-contents

Recommendation Systems

1. https://app.pluralsight.com/library/courses/algorithms-recommendation-systems/table-of-contents
2. https://github.com/guymorita/recommendationRaccoon
3. https://github.com/apache/predictionio/

Anomaly Detection

1. https://towardsdatascience.com/outlier-detection-with-isolation-forest-3d190448d45e
2. https://www.quora.com/What-is-the-difference-between-random-forest-and-isolation-forest
3. https://stackoverflow.com/questions/43063031/how-to-use-isolation-forest
4. https://quantdare.com/isolation-forest-algorithm/
5. https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/one-class-support-vector-machine
6. https://www.kaggle.com/mlg-ulb/creditcardfraud/kernels

Cheatsheets & Aggregations

1. https://medium.com/machine-learning-in-practice/cheat-sheet-of-machine-learning-and-python-and-math-cheat-sheets-a4afe4e791b6
2. https://medium.com/machine-learning-in-practice/learning-machine-learning-and-nlp-from-185-quora-questions-cebe42e47da8
3. https://medium.com/machine-learning-in-practice/my-curated-list-of-ai-and-machine-learning-resources-from-around-the-web-9a97823b8524

Model Serialization

1. https://medium.freecodecamp.org/a-beginners-guide-to-training-and-deploying-machine-learning-models-using-python-48a313502e5a

Miscellaneous References

1. https://gab41.lab41.org/the-10-algorithms-machine-learning-engineers-need-to-know-f4bb63f5b2fa
2. https://medium.com/machine-learning-in-practice/cheat-sheet-of-machine-learning-and-python-and-math-cheat-sheets-a4afe4e791b6
3. https://medium.com/machine-learning-in-practice/my-curated-list-of-ai-and-machine-learning-resources-from-around-the-web-9a97823b8524
4. https://medium.com/machine-learning-in-practice/learning-machine-learning-and-nlp-from-185-quora-questions-cebe42e47da8
5. https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A
6. https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months
7. https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook
8. https://github.com/kudkudak/python-for-data-processing
9. https://github.com/dipanjanS/practical-machine-learning-with-python
10. https://medium.com/fintechexplained/end-to-end-guide-for-machine-learning-project-146c288186dc

Important Websites

1. https://www.kaggle.com/
2. https://www.analyticsvidhya.com/
3. https://ai.google/education/
4. http://scikit-learn.org/stable/tutorial/index.html
5. https://github.com/josephmisiti/awesome-machine-learning

Datasets

1. https://archive.ics.uci.edu/ml/index.php