👶 Technical concepts explained in layman terms! git.io/eli5
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Oct 26, 2023
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eli5
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A set of tools for leveraging pre-trained embeddings, active learning and model explainability for effecient document classification
python sklearn word-embeddings document-classification flair active-learning model-interpretation eli5 document-classifier model-interpretability
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Jan 23, 2025 - HTML
Build a Web App called Menara to Predict, Forecast House Prices and search GreatSchools in California - Bay Area
python machine-learning deep-learning time-series neural-network sklearn supervised-learning aws-ec2 unsupervised-learning haversine-formula lime eli5 haversine-distance shap streamlit
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Feb 20, 2024 - Jupyter Notebook
Graduation Project - Sentiment Mining
nlp random-forest word-embeddings logistic-regression glove adaboost t-sne sparse-vectors fasttext support-vector-machines ensemble-model w2v sentiment-classification multinomial-naive-bayes eli5 fine-tuning elmo d2v
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Dec 5, 2019 - Python
This is a repository for reproducibility purposes. In this research, a large number of datasets were used to create different ML models, which were then explained by XAI measures. Seeking to identify situations where XAI measures agreed or disagreed with each other.
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Dec 20, 2023 - Jupyter Notebook
A telegram channel parser + binary text classifier utilizing a simple logistic regression model
telegram parsing text-classification scikit-learn sklearn logistic-regression regular-expressions openpyxl binary-classification tqdm classifier-model eli5 sklearn-library nltk-python telegrambot-python
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Sep 13, 2023 - Jupyter Notebook
E-Commerce Comment Classification with Logistic Regression and LDA model
latent-dirichlet-allocation latent-semantic-analysis pyldavis eli5 bag-of-features sentiment-prediction
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Dec 14, 2018 - Jupyter Notebook
This problem is a typical Classification Machine Learning task. Building various classifiers by using the following Machine Learning models: Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), XGBoost (XGB), Light GBM and Support Vector Machines with RBF kernel.
python random-forest numpy svm sklearn eda pandas seaborn xgboost lightgbm logistic-regression decision-trees lime eli5 gridsearchcv auc-roc-curve shap auc-roc-score skit-learn
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Dec 16, 2022 - Jupyter Notebook
How does Word2Vec work ?
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Nov 15, 2017 - Jupyter Notebook
Machine Learning Feature-Importance Using SHAP and eli5
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Jan 16, 2023 - Jupyter Notebook
2022년 1학기 개인 프로젝트 : 뇌졸증 환자 예측 모델·분석
numpy sklearn pandas seaborn matplotlib statsmodels eli5 feature-importance imbalanced-dataset stroke-prediction
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Feb 17, 2024 - Jupyter Notebook
This project aims to explore satellite image dataset in order to create a CNN model for wildfire prediction problem. Explainability with ELI5 and GradCAM could be an interesting integration to be tested.
data-science deep-learning cnn classification transfer-learning eli5 satellite-images wildfire-prevention
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Jul 1, 2024 - Jupyter Notebook
Learning to represent text using Word2Vec
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Feb 19, 2018 - Jupyter Notebook
Exploring feature contributions to outliers, feature importances, and image recognition features
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Nov 21, 2022 - Jupyter Notebook
This project aims to predict the Taxi-trip duration within NYC based on several factors as predictors. Various combinations of relevant features are explored as iterations. After analysing the dataset, important and necessary features are selected. Several regression models are implemented & evaluated based on R2 & RMSE, & predictions visualised
python sklearn regression pandas xgboost lightgbm folium geopandas chi-square-test decision-tree-regression eli5 nyc-taxi-dataset anova-test stacking-ensemble
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Jul 21, 2023 - Jupyter Notebook
na podstawie kursu "Matrix - poznaj reguły gry", stworzonego przez DataWorkshop
data-science machine-learning random-forest decision-tree decision-tree-regression eli5 kfold-cross-validation dataworkshop datadotworld
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Jun 13, 2020 - Jupyter Notebook
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