Analysis and Implementation of Machine Learning Models and Methods
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Updated
Mar 22, 2017 - Jupyter Notebook
Analysis and Implementation of Machine Learning Models and Methods
The Labelled Transition Systems Extractor tool project
Learn about Feature Engineering and get familiar with Advanced regression techniques like Lasso, ElasticNet, Gradient Boosting, etc.
Visual analysis of models based on input and outputs.
1st Software Specification Project
Developed a machine learning model to identify fraudulent credit applications, with a Fraud Detection Rate of 56.12% at 3% of the population. The resulting model can be utilized in a credit card fraud detection system.
An alternative to MCMC for rapid analysis of models
MADS (Model Analysis & Decision Support) documentation
This analysis refers to uncertainity, both model uncertainity and data uncertainity.
Toolbox to analyze temporal context invariance of deep neural networks
Visualize the filters of a pre-trained model and analyze which portion of the image contributes most to the overall detection.
Adult-Child Musculoskeletal Model and Motion Analysis.
Dynamic Spectrotemporal Receptive Field (dSTRF) Analysis Toolbox
pycalibrate is a Python library to visually analyze model calibration in Jupyter Notebooks
The official code and dataset for EMNLP 2022 paper "COPEN: Probing Conceptual Knowledge in Pre-trained Language Models".
Zaključno nalogo Modelske analize 2
Some code for my Physics of Fission Reactors model analysis reports, written in MATLAB and Python
Support Vector Regression for Unsupervised Machine Learning
📚 🐣 软件实践文集。主题不限,思考讨论有趣有料就好,包含如 系统的模型分析/量化分析、开源漫游者指南、软件可靠性设计实践、平台产品的逻辑与执行… 🥤
A Julia package for mapping qualitative data patterns to regions of a model's parameter space.
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