Machine Learning Model to predict student graduation grade

Repository riset untuk Minggu 1 Bulan Oktober

Detect public transport modes using different ML models.

Bu çalışmamda "Makine Öğrenmesi" algoritmaları üzerine çalıştım. Bu algoritmaları veri seti üzerinde uygulayarak tahminlerde bulundum ve sonuçları analiz ettim.

Very useful image related utilities

Evaluation for object detection models

Script to compute Precision, Recall, AvP and MAP and to plot PR curves in the context of Information Retrieval evaluation.

my implementation calculate precision, recall, f1, accuracy, and GLEU score

Accurately predicting companies' future failure with Python.

Directing Sentiment and Evoking Recall in GPT-2 from an Attention Bock Based Persistent Memory using a Small Fraction of One Layer and a Case for the Spacial Separation of what might be described as Emotional Implicit Memory and Explicit Memory

Librecall, or Libre Recall is an open-source alternative to Microsoft's Windows Recall feature for Linux and Windows

Summarize your meetings with the power of Recall AI.

A repository to understand ranking metrics as described by Musgrave et al. (2020). Plus some other metrics utilising confidence values.

Better multi-class confusion matrix plots for Scikit-Learn, incorporating per-class and overall evaluation measures.

Precision-recall-gain for Python

A tiny app to log the active Windows title to a desktop log file in a windows system

⬅️📽️ App inspired by Windows Recall for creating duplicate screenshots with text recognition and the ability to search through screenshots.

Evaluation and agreement scripts for the DISCOSUMO project. Each evaluation script takes both manual annotations as automatic summarization output. The formatting of these files is highly project-specific. However, the evaluation functions for precision, recall, ROUGE, Jaccard, Cohen's kappa and Fleiss' kappa may be applicable to other domains too.

Program where you can draw patterns in an nxn grid. Afterwards you can store and recall them using a Hopfield network.

This code build up a predicting model use the Machine learning algorithms such as Decision Tree, k-Nearest Neighbors etc. on the Vehicle to predict the departure action