duartebianca

duartebianca's Stars

• hoptical/nodegraph-api-plugin

  A data source plugin for nodegraph panel in grafana

  Language:TypeScript7114

• LABORA-INF-UFG/openran-br-blueprint

  Language:Python61

• 5GSEC/OSC-RIC-xApp-Template

  xApp Python development template for O-RAN SC RIC

  Language:Python1

• onosproject/onos-e2t

  E2 AP Termination module for ONOS SD-RAN (µONOS Architecture)

  Language:Go519

• Valdecy/pyMetaheuristic

  pyMetaheuristic: A Comprehensive Python Library for Optimization

  Language:Python31974

• Doriandarko/RepoToTextForLLMs

  Automate the analysis of GitHub repositories for LLMs with RepoToTextForLLMs. Fetch READMEs, structure, and non-binary files efficiently. Outputs include analysis prompts to aid in comprehensive repo evaluation

  Language:Python65286

• onosproject/onos-ric-sdk-py

  Python Application SDK for ONOS RIC (µONOS Architecture)

  Language:Python118

• google-gemini/cookbook

  Examples and guides for using the Gemini API

  Language:Jupyter Notebook4.9k706

• google/generative-ai-docs

  Documentation for Google's Gen AI site - including the Gemini API and Gemma

  Language:Jupyter Notebook1.6k568

• yasmimvso/processamento-imagem

  Estudos sobre processamento de imagem utilizando bibliotecas do python.

  Language:Python1

• o-ran-sc/sim-ns3-o-ran-e2

  Language:C++4015

• JeevanSandhu/Intrusion-Detection

  Intrusion Detection using various Data Mining Techniques (KDD Cup 1999 Data)

  Language:Python1610

• Y-oHr-N/OptGBM

  Optuna + LightGBM = OptGBM

  Language:Python347

• optuna/optuna

  A hyperparameter optimization framework

  Language:Python10.7k1k

• sk-t3ch/catboost-quickstart

  🐈 🚀 Quickstart machine learning notebooks for creating CatBoost models

  Language:Jupyter Notebook51

• mayank408/TFIDF

  Implementation of TF-IDF from scratch in Python

  Language:Jupyter Notebook105105

• turkalpmd/CatBoost_SHAP_SMOTE

  Of all the applications of artificial intelligence, diagnosing any disease using a "black box" is always going to be a hard explanation. Those who will use the application will want to know how the model decides on the treatment conditions or following-up conditions according to the model result. Or data provider clinicians will want the model with the highest performance in their project. This dataset classified patients according to sacral position properties. I investigated using the below techniques for the best result and explainable machine learning model; Balancing unbalanced medical data Creating models with CatBoost Classifier Finding the most optimized parameters by Grid Search with the Optuna library Artificial intelligence algorithms described as Black Box are actually explainable SHAP library tutorial Combined use of RFECV and SHAP library for Feature Selection Comparison of all applied models to each other

  Language:Jupyter Notebook1

• optuna/optuna-examples

  Examples for https://github.com/optuna/optuna

  Language:Python675176

• Rivercan/feature_selection

  feature selection by using random forest.

  Language:Python116

• dwpsutton/rf_select

  Feature selection tool using random forest variable importance measures.

  Language:Python164

• arnaldog12/Machine_Learning

  Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

  Language:Jupyter Notebook21964

• dataprofessor/langchain-ask-the-data

  Build an LLM powered Ask the Data App with LangChain (using the Pandas DataFrame Agent) and Streamlit

  Language:Python2821

• alura/techguide

  TechGuide main repository with the code that guides your tech career!

  Language:TypeScript3.5k706

• gabrielnogueiralt/IF678-InfraCom

  Provas, projetos, exercícios e materiais utilizados na disciplina IF678, CIn - UFPE (2020.3)

  Language:Java1

• krmanik/genanki-js

  A JavaScript implementation for generating Anki decks in browser client side

  Language:JavaScript546

• iuricode/padroes-de-commits

  Padrões de commits

  Language:Shell5.6k946

• NdYAG/anki-apkg

  Create .apkg file for Anki

  Language:TypeScript368

• patarapolw/ankisync2

  Creating and editing *.apkg and *.anki2 safely

  Language:Python7412

• repeat-space/anki-apkg-export

  :book: Generate decks for Anki (spaced repetition software)

  Language:JavaScript14540

• myscale/ChatData

  ChatData 🔍 📖 brings RAG to real applications with FREE✨ knowledge bases. Now enjoy your chat with 6 million wikipedia pages and 2 million arxiv papers.

  Language:Python15411