tdl77 Goto Github PK

explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

eye_of_retail_itmo

Hackaton Project

face_classification

Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.

fancyimpute

Multivariate imputation and matrix completion algorithms implemented in Python

fastapi_course

Вводный курс по фреймворку FastAPI на YouTube

fastauc

Three fast ROC AUC calculation implementations for python

fault-detection-for-predictive-maintenance-in-industry-4.0

This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

featseltutorial

Python notebooks for the tutorial paper on feature selection

feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

feature-engineering-for-time-series-forecasting

feature-selection-cqm

Use a hybrid solver to select features from two data sets

feature-selector

Feature selector is a tool for dimensionality reduction of machine learning datasets

featureselectionga

Feature Selection using Genetic Algorithm (DEAP Framework)

fiftyone

The open-source tool for building high-quality datasets and computer vision models

finampy

Библиотека-обертка, которая позволяет работать с функционалом Comon Trade API брокера Финам из Python

financial-machine-learning

A curated list of practical financial machine learning tools and applications.

findpeaks

The detection of peaks and valleys in a 1d-vector or 2d-array (image)

finec

Financial data and computation for Finec MGIMO students.

france_energy_demand_prediction_and_forecast_model_-ml_module_capstone_company_project-

Key functionality and highlights:  The created Machine learning model is useful in planning daily energy producing operations, balancing demand with adequate supply, thus fulfil Frances’ energy demands, and finally prevent generation of excess energy.  The model is structured to make predictions two days ahead. With a MAPE of 1.47% and Accuracy of ~94% CNN  CNN, MLP, RF, KNN and LR has been used for both prediction and Forecast. RF and LR produced and accuracy of 99% for one hour ahead prediction and MLP an accuracy of ~93% for two days ahead forecast.

fraud-detection-project

freegpt-webui

GPT 3.5/4 with a Chat Web UI. No API key required.

functime

Time-series machine learning and embeddings at scale.

fuxictr

A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io/tutorials

gan-for-tabular-data

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

gauss-rank-scaler

Scikit-learn compatible implementation of the Gauss Rank scaling method

genetic_algorithm

Application of genetic algorithm in feature selection.

geneticfs

GeneticFS is a library for feature selection in Machine Learning using a Genetic Algorithm as an optimisation method.

german-traffic-sign-recognition-with-deep-learning

Recognizing traffic signs with deep learning and PyTorch using Spatial Transformer Convolutional Neural Networks.

gif

The matplotlib Animation Extension

grad-cam

[ICCV 2017] Torch code for Grad-CAM