Contians articles relating to more than Data Science.

https://learn.g2.com/

University of Michigan - Ann Arbor

This node can be used to share and reference helpful articles that are machine learning specific, as opposed cover the broad domain of data science.

Machine Learning Helpful Online Articles

https://expertsystem.com/machine-learning-definition/

Useful website about understanding machine learning

This online article provides a deep dive into what software engineers should be doing before applying machine learning practices and is written at the level for anyone who has some basic machine learning knowledge. Dr. Martin Zinkevich shares the knowledge he has accumulated from working at Google, particularly in machine learning applications in software engineering.

http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf 

Rules of Machine Learning: Best Practices for ML Engineering

This article provides a practiced method of addressing the issue of data leakage in machine learning. Their two step procedure of identifying and preventing data leakage is essential for machine learning scientists to consider in order to produce models with high generalization ability.

Kaufman, S., Rosset, S., & Perlich, C. (2011). Leakage in data mining. Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11. doi:10.1145/2020408.2020496

http://www.cs.umb.edu/~ding/history/470_670_fall_2011/papers/cs670_Tran_PreferredPaper_LeakingInDataMining.pdf 

Leakage in Data Mining: Formulation, Detection, and Avoidance

Developers need to know what works and how to use it. This site uses less math and more tutorials with working code.
https://machinelearningmastery.com/

Machine Learning Mastery

https://towardsdatascience.com/beyond-accuracy-precision-and-recall-3da06bea9f6c

Useful Article about statistical methods of performance evaluation

Sharing concepts, ideas and codes.
https://towardsdatascience.com/

Towards Data Science

Learning Hub

https://magnimindacademy.com/blog/deep-learning-and-its-5-advantages#:~:text=One%20of%20the%20biggest%20advantages,told%20to%20do%20so%20explicitly.

DEEP LEARNING AND ITS 5 ADVANTAGES

https://www.nature.com/articles/s41598-020-76550-z

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images

https://stats.stackexchange.com/questions/45087/why-doesnt-backpropagation-work-when-you-initialize-the-weights-the-same-value

Initialize the weights with the same value

https://www.educative.io/edpresso/what-are-overflow-and-underflow

What are overflow and underflow?

https://www.deeplearning.ai/ai-notes/initialization/

Proper way of Initializing neural networks

https://www.rfwireless-world.com/Terminology/Advantages-and-Disadvantages-of-Deep-Learning.html#:~:text=Following%20are%20the%20drawbacks%20or,GPUs%20and%20hundreds%20of%20machines.

Key drawbacks/disadvantage of deeplearning

Predicting the Computational Cost of Deep
Learning Models

https://www.aclweb.org/anthology/D19-1594.pdf

Text Genre and Training Data Size in Human-Like Parsing

https://en.wikipedia.org/wiki/BERT_(language_model)

BERT (language model)


https://towardsdatascience.com/bert-explained-state-of-the-art-language-model-for-nlp-f8b21a9b6270

BERT Explained: State of the art language model for NLP

http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf

Rules for machine learning

Amin, M., & Burghardt, M. (2020, December). A survey on approaches to computational humor generation. In Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (pp. 29-41).

Learn Before

Related