2022학년도 AI 인력양성 과정 (알고리즘으로 풀어보는 신경망, 딥러닝)
-
Updated
Jul 29, 2022 - Jupyter Notebook
2022학년도 AI 인력양성 과정 (알고리즘으로 풀어보는 신경망, 딥러닝)
This is a section of the project to learn the machine to predict data.
Machine Learning & Deep learning
Laboratory with random forest, logistic regression and SVM. The dataset used for this test is a set of points generated randomly with the following specification: • Number of Samples: 1200 • Number of Classes: 3 • Number of Features: 2 (Length and Width).
Projeto final da disciplina de Machine Learning (2022.2).
We're going to classify and predict the "Stage" value, which is either Won or Lost, of a dataset containing auction records, using scikit-learn’s library and algorithms such as decision trees, random forests, naïve Bayes, and KNN.
Titanic Kaggle Competition
L'objectif de cette étude est de définir à partir des enquêtes d'insertion professionnelles réalisé par le ministère de l'enseignement supérieur si le salaire moyen annuel brut permet lmoyen permet de faire partie des 30% des français les plus riches
This project aims to build an AI agent to recognize handwritten digits using machine learning algorithms. The agent will extract the handwritten text from an image and classify it into their respective digit labels using a machine learning module trained upon the MNIST dataset by the SVM algorithm.
3 Tasks of Oasis Infotype remote intern in data science
this repository contains two projects : the first it s applying ML algorithm (Logistic regression) for classification on Titanic dataset From scratch and with use Sickit-Learn and the second for analyze this data : Understanding data - data preprocessing
This is a "Big Mart Sales Prediction Project" using python programming language.
A very simple neural network implementation in python.
The code below is for a machine learning project that builds a regression model using different algorithms and evaluates their performance.
End-to-End Machine Learning/Data Science Project
Machine Learning model trained to predict prices of real estate properties in Belgium
This project involves cohort analysis and customer segmentation to help an e-commerce giant improve its product offerings, customer relations and maximize profit.
persian Ham Spam detector with python, hazm, nltk and nlp.
The project involves analyzing transactions and classifying them into fraudulent and non-fraudulent through Machine Learning techniques.
Add a description, image, and links to the sickit-learn topic page so that developers can more easily learn about it.
To associate your repository with the sickit-learn topic, visit your repo's landing page and select "manage topics."