Own implementation of SVM classifier solving dual optimization problem
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Updated
Apr 12, 2024 - HTML
Own implementation of SVM classifier solving dual optimization problem
ResumeRevealer is an advanced tool designed for HR professionals, recruiters, and hiring managers to streamline the process of resume parsing and candidate evaluation. It offers a comprehensive solution to extract valuable insights from diverse resume formats, standardize job titles, and mine detailed skills from project descriptions.
this project utilizes Python for the screening of resumes. It involves data cleaning, visualization, and machine learning techniques to categorize resumes into different job categories.The project achieves high accuracy using a machine learning algorithm, showcasing its effectiveness in automating the resume screening process.
This GitHub repository provides an implementation of the paper "MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network" . MAGNET is a state-of-the-art approach for multi-label text classification, leveraging the power of graph neural networks (GNNs) and attention mechanisms.
Cancer prediction system using machine learning algorithm and training the model on different gene expression of cancer
Tag Prediction Model for the Doubt Asking Platform. Suggests tags based on the user input question and question description.
Logistic regression model to sort Hogwarts students into their perspective houses based on their performance in classes.
Base de dados que será utilizada para treinamento de uma rede perceptron.
Реализация метода опорных векторов для классификации данных
Using ML Classification to predict customer segmentation groups
Contains models implemented from scratch and a project implemented from end-to-end
Binary Classification Models with pySpark in Apache Spark
This is a Machine learning project for screening of resumes based on the type of job and the content with the help of NLP techniques.
A machine learning model that predicts tags for a given question and body.
A multi-class classification problem where the objective is to read a question posted on the popular reference website, StackOverflow and predict the primary topics it deals with, i.e. tags which the question will be associated with.
Classifying a tweet as positive, neutral, or negative sentiment using Natural Language Processing (CBOW approaches) and Traditional Machine Learning Algorithms.
Harry Potter and a Data Scientist: Write a multi-class classifier using gradient descent optimization algorithm to replace the bewitched Sorting Hat and save Hogwarts! 🎩🧙♂️
A PySpark MLlib classification model to classify songs based on a number of characteristics into a set of 23 electronic genres.
Using NLP or prediction of stack overflow posts using linear models for multi-class classification
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