Context: On top of the inherent challenges startup software companies face applying proper software engineering practices, the non-deterministic nature of machine learning techniques makes it even more difficult for machine learning (ML) startups....
500 AI Machine learning Deep learning Computer vision NLP Projects with code (⭐ 32078)
Predicting property and casualty insurance claims: A Machine Learning Approach (⭐ 6)
Code repository for the O'Reilly publication "Building Machine Learning Pipelines" by Hannes Hapke & Catherine Nelson (⭐ 609)
Last Minute Note of Machine learning and Deep learning by Jason Brownlee (⭐ 92)
Python code for common Machine Learning Algorithms (⭐ 4562)
Thousands of everyday sounds, organized using machine learning. (⭐ 760)
Machine Unlearning (MU) has emerged as a promising approach to addressing persistent challenges in Machine Learning (ML) systems. By enabling the selective removal of learned data, MU introduces protective, corrective, and adaptive capabilities that...
This Project is to make an automated Teller machine with user's Account Number, and Password, bank account, with that users can withdraw, deposit, and view their account balance. (⭐ 242)
Neural Machine Translation (NMT) models are state-of-the-art for machine translation. However, these models are known to have various social biases, especially gender bias. Most of the work on evaluating gender bias in NMT has focused primarily on En...
The "Python Machine Learning (3rd edition)" book code repository (⭐ 4998)
The "Python Machine Learning (2nd edition)" book code repository and info resource (⭐ 7205)
Code Repository for Machine Learning with PyTorch and Scikit-Learn (⭐ 5028)
The "Python Machine Learning (1st edition)" book code repository and info resource (⭐ 12595)
Notes on Advances in Financial Machine Learning (⭐ 84)
Gremlin is a graph traversal machine and language designed, developed, and distributed by the Apache TinkerPop project. Gremlin, as a graph traversal machine, is composed of three interacting components: a graph $G$, a traversal $Ψ$, and a set of tr...
We study the problem of troubleshooting machine learning systems that rely on analytical pipelines of distinct components. Understanding and fixing errors that arise in such integrative systems is difficult as failures can occur at multiple points in...
Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison (⭐ 780)
Course material for STAT 479: Machine Learning (FS 2018) at University Wisconsin-Madison (⭐ 503)
Low-resource languages (LRLs) face challenges in supervised neural machine translation due to limited parallel data, prompting research into unsupervised methods. Unsupervised neural machine translation (UNMT) methods, including back-translation, tra...