Durveshbaharwal/Enhanceing_GPS_ML

Enhancing GPS Positioning Accuracy Using Machine Learning

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Suundumused/Weather-Forecast-AI-Example

The project scope is a weather forecasting model based on behavioral analysis of the last 33 hours (hour-by-hour forecast) with Random Forest Classifier. The program automatically saves and loads the last trained model for prediction.

Language: Python - Size: 4.36 MB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 1 - Forks: 0

07raghavan/threat-detection-

This repository contains a deep learning-based audio classification project using Convolutional Neural Networks (CNNs). The model processes audio signals, extracts relevant features like spectrograms classifies them into predefined categories. Which will be used to detect threats in the forest such as gunshots, vehicle movement, wood cutting.

Language: Python - Size: 23.4 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 1 - Forks: 0

DurgasaiKoda/fish-disease-detection

🐟 Fish Disease Detection using Streamlit and Machine Learning. Upload fish images to detect diseases using trained ML models (SVM, Random Forest, XGBoost, etc.). Models are auto-cached and compared with dynamic accuracy visualization.

Language: Python - Size: 705 KB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0

Tdeniz1/heart-disease-ml

Machine learning heart disease predictor.

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Any11222/CodeClauseInternship_Customer-Segmentation-with-K-Means-Clustering

Customer segmentation using K-Means clustering on mall customer data. Visualizations, analysis, and CSV output included.

Language: Python - Size: 57.6 KB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 0 - Forks: 0

Assa-45/bananaquality-prediction

Streamlit App for predicting banana's quality

Language: Python - Size: 1.22 MB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

bloom121/uci-marketing-analysis-cart

UCI bank marketing data analysis with decision trees (CART).

Language: Python - Size: 77.1 KB - Last synced at: 24 days ago - Pushed at: 24 days ago - Stars: 0 - Forks: 0

dimitrismistriotis/alt-profanity-check Fork of vzhou842/profanity-check

A fast, robust library to check for offensive language in strings, dropdown replacement of "profanity-check".

Language: Python - Size: 64.3 MB - Last synced at: 18 days ago - Pushed at: about 2 months ago - Stars: 76 - Forks: 17

Shantanudhanawade/Mini-projects

Price prediction with linear regression

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andleebfama/Data-Preprocessing

This project focuses on data preprocessing of the Titanic dataset, which is a crucial step in any data analysis or machine learning workflow. The goal is to clean the raw data by handling missing values, converting categorical data into numeric format, and normalizing numerical features.

Language: Python - Size: 42 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Abdelrahman-Atef-Elsayed/Iris-Flower-Classification

Simple machine learning project for classifying Iris flowers using scikit-learn. A beginner-friendly ML project with multiple models comparison (Decision Tree, SVM, etc.)

Language: Python - Size: 16.6 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

aditybarnwal22/Lung-Cancer-Prediction-App

This project, titled “Lung Cancer Prediction,” presents a web-based application that enables preliminary risk assessment for lung cancer using Machine Learning Algorithms.

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narendhiran-dev/Predictive-Analytics-for-Repayment-Predictions

A machine learning API built with Python, FastAPI, and Scikit-learn to predict borrower repayment risk based on historical payment data. A FinTech risk assessment system that uses a Random Forest model to predict a borrower's future repayment behavior and serves the prediction via a REST API.

Language: Python - Size: 10.7 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

mikekeith52/scalecast

The practitioner's forecasting library

Language: Python - Size: 1.16 GB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 339 - Forks: 40

microsoft/ML-For-Beginners

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

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dataprofessor/code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

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niitsuma/delayedsparse

Efficient sparse matrix implementation for various "Principal Component Analysis"

Language: Python - Size: 26.4 KB - Last synced at: 18 days ago - Pushed at: over 6 years ago - Stars: 12 - Forks: 2

IAmJuniorB/D499-Supervised-Learning

This class for machine Learning presents the end-to-end process of investigating data through a machine learning lens.

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Haseeeb21/Machine-Learning-Models

Machine Learning Models trained on Scikit-learn datasets. This repository contains the code files and saved models trained on Toy datasets (Classification & Regression), and Real World dataset.

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aabbtree77/uci-marketing-analysis-cart

UCI bank marketing data analysis with decision trees (CART).

Language: Python - Size: 77.1 KB - Last synced at: about 7 hours ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

LatiefDataVisionary/scikit-learn-with-indonesia-belajar

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SuperKogito/Voice-based-speaker-identification

:sound: :boy: :girl: :woman: :man: Speaker identification using voice MFCCs and GMM

Language: Python - Size: 105 KB - Last synced at: 2 months ago - Pushed at: over 4 years ago - Stars: 54 - Forks: 15

SuperKogito/Voice-based-gender-recognition

:sound: :boy: :girl:Voice based gender recognition using Mel-frequency cepstrum coefficients (MFCC) and Gaussian mixture models (GMM)

Language: Python - Size: 8.96 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 213 - Forks: 68

vatsalmehta2001/wine_quality_prediction

End-to-end machine learning project predicting wine quality based on chemical properties, featuring data exploration, feature engineering, model optimization, and an interactive Streamlit interface.

Language: Python - Size: 36.2 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

BaseMax/ImageRecognitionAI

Recognition of the images with artificial intelligence includes train and tests based on Python.

Language: Python - Size: 31.3 KB - Last synced at: 10 days ago - Pushed at: 11 months ago - Stars: 14 - Forks: 7

suleymancgn/NLP-SentimentClassification

NLP-SentimentClassification is a repository for natural language processing projects focused on analyzing and classifying sentiment in text data using various machine learning techniques. It provides code examples and resources for training models to accurately predict sentiment in text-based data sources.

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jdonepud/NLP-SentimentClassification

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azevedontc/scikit-learnLibrary

scikit-learn Library (sk-learn) / Biblioteca scikit-learn (sk-learn)

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OCHOLA-EDDYPHIL/Clustering

This project performs hierarchical clustering on a dataset containing network usage and performance metrics. It includes data preprocessing, encoding, normalization, and visualization of clustering results using dendrograms. The purpose is to analyze and group similar data points, offering insights into patterns and relationships within the dataset

Language: Python - Size: 19.5 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

brandipessman/PyCharm_Python_Course

Learned to use python for data science, machine learning, automation, and game/app/web development through 100 day intensive course.

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priyaa98/Projects

Topics related to Machine Learning

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reddyprasade/Machine-Learning-with-Scikit-Learn-Python-3.x

In general, a learning problem considers a set of n samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dimensional entry (aka multivariate data), it is said to have several attributes or features. Learning problems fall into a few categories: supervised learning, in which the data comes with additional attributes that we want to predict (Click here to go to the scikit-learn supervised learning page).This problem can be either: classification: samples belong to two or more classes and we want to learn from already labeled data how to predict the class of unlabeled data. An example of a classification problem would be handwritten digit recognition, in which the aim is to assign each input vector to one of a finite number of discrete categories. Another way to think of classification is as a discrete (as opposed to continuous) form of supervised learning where one has a limited number of categories and for each of the n samples provided, one is to try to label them with the correct category or class. regression: if the desired output consists of one or more continuous variables, then the task is called regression. An example of a regression problem would be the prediction of the length of a salmon as a function of its age and weight. unsupervised learning, in which the training data consists of a set of input vectors x without any corresponding target values. The goal in such problems may be to discover groups of similar examples within the data, where it is called clustering, or to determine the distribution of data within the input space, known as density estimation, or to project the data from a high-dimensional space down to two or three dimensions for the purpose of visualization (Click here to go to the Scikit-Learn unsupervised learning page).

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PREMRAJESH/Machine_learning_notes

Machine Learning libraries tutorial and basics notes

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ViniciusMassari/regressao_linear_multipla

Prediction of a cholesterol exam based in some features about the patient

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Niroop2004/Real_estate_price_prediction.

This Flask app predicts house prices using a RandomForestRegressor model trained on a housing dataset. It includes data pre-processing with pipelines and imputers, stratified train-test splitting, and a user input form. Predictions are displayed on the web page, making it ideal for learning basic machine learning deployment with Flask.

Language: Python - Size: 127 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

mongshil553/Scikit-Learn-Clustering

Sleep Health and Lifestyle Clustering using Scikit-Learn

Language: Python - Size: 3.14 MB - Last synced at: 5 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

lixcli/simple_classification_of_hanzi

simple classification of hanzi by scikit-learn

Language: Python - Size: 12 MB - Last synced at: about 1 year ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0

JamshedAli18/Introduction-To-Machine-Learning

A Course from kaggle solved Exercises

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SubhangiSati/Machine-Learning

This consists of various machine learning algorithms like Linear regression, logistic regression, SVM, Decision tree, kNN etc. This will provide you basic knowledge of Machine learning algorithms using python. You'll learn PyTorch, pandas, numpy, matplotlib, seaborn, and various libraries.

Language: Python - Size: 17.6 KB - Last synced at: about 2 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

my-thought-experiments/explore-scikit-learn

A collection of documents and programs to learn about Data Science and ML using Scikit-learn.

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AjayZinngg/simple-nltk-chatbot

A Q&A based chatbot which queries the database to find responses for similar questions asked by the users

Language: Python - Size: 35.2 KB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 2 - Forks: 0

yporquenoahora/Recomendador-Front

Buscador y recomendador del catálogo de películas de Filmin

Language: Svelte - Size: 4.7 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

YasserBar/IR-Search-Engine

Search Engine with Python, NLTK, and Scikit-learn

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RobertLupas/SentiSense

An AI model built to understand the sentiments transmitted through a phrase.

Language: Python - Size: 6.84 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

AM-mirzanejad/Heart-Failure-Prediction

The Heart Disease Predictor is a Python project developed to classify whether an individual has heart disease based on specific input parameters. It utilizes the scikit-learn and NumPy libraries for implementation.

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soham6125/SMART-Metro

A website powered by Machine Learning to dynamically predict the shortest and safest route from source to destination.

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stevenhastings/TweetyPy

Full-Stack application that allows client to use a predictive model to determine which user is more likely to have tweeted a given text. This project covers everything from API's to Predictive Modeling, SQLAlchemy database storage, Flask, along with other full-stack components. In the end it is deployed for online usage using Heroku.

Language: Python - Size: 36.8 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

Thamine-sumaya/Jornada-Python

Mini curso - Jornada Python oferecido pela hashtag treinamentos - 4 projetos em Python

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alanbluefox/pyprog

python programming following lessons on Aurelien Geron book "Hands on ML"

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chandakakshat/Digital-Kisaan-Portal

A web application designed to support farmer-community with Intelligent Machine Learning technologies, providing live crop recommendation and prediction system, facilitating farmers with online community support and chat bot based on Artificial Intelligence. It also Integrates an on-demand news feed page aiding for socializing within the farmer community.

Language: Jupyter Notebook - Size: 9.33 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 1

NajiAboo/TextClassification

Build custom vacab, Ham /Spam using tfidf , Movie review classification using TFIDF

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ShwetaBhattacharjee/Used-Car-Price-Prediction

Collected and classify the used car data from the Dhaka city. Used scikit-learn python toolkit for statistical modeling including classification, regression and predicted new and old car's selling price. This can be a helpful tool for used car selling companies.

Language: Python - Size: 2.93 KB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

Edai/MLNetworkEmbedding

Several implementation of ML network embedding and graph embedding

Language: Python - Size: 6.05 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0

thamizhannal/INSOFE

Works done at International School of Engineering

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sanchitvaid/Housing-Data-analysis

Exploratory data analysis of housing data using Python

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kaidalisohaib/AICohortW24

Winter24AICohort

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AbhishekRS4/ML_water_potability_fastapi_deployment

ML model application deployment using FastAPI with MLOps using MLFlow for water potability dataset

Language: Python - Size: 7.64 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Jeyjocar/Redes-Neuronales

24/01/2024 Jeyfrey J. Calero R. Aplicación de Redes Neuronales con scikit-learn streamlit, pandas, seaborn y matplolib

Language: Python - Size: 360 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

charlie2951/mL_Rpi_ZeroW

Machine Learning on Raspberry Pi Zero and Zero-W

Language: Python - Size: 479 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

waldvoid/spotifyProject

Spotify Playlist Music Recommendation System

Language: Jupyter Notebook - Size: 94.1 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

e19931107/Scikit_Learn-Diabetes

Language: Python - Size: 148 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

21sult/recipe-site-traffic

Data Science and Machine Learning project for a recipe website that wishes to increase their traffic.

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Go-MinSeong/Predicting-whether-your-mail-will-be-read

predicting whether you read mail

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ohmthanap/CS513_Knowledge-Discovery-Data-Mining

Learned techniques and tools for Knowledge Discovery and Data Mining: R, RStudio, Classification Models

Language: R - Size: 38.7 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Aroojzahra908/Artifical-Intelligence-and-Machine-Learning-

Explore the basics of linear regression, gradient descent, and AI using Python. Get hands-on with NumPy, pandas, Matplotlib, and scikit-learn for practical learning.

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rifatSDAS/satellite_machine_learning

Unsupervised and supervised learning for satellite image classification

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PrathamGhoshRoy/Titanic-MLfromDisaster

A ML learning approach with increasing complexity.

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princessnaya1234/ML-House-Prices-Prediction-Model

A trained ML model for prediction of house prices in IOWA using Random Forest Regression technique

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tanvirnwu/ML-Algorithms--Scikit-learn--Python

This folder contains the basic algorithms of ML implemented with Python.

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flo7up/relataly-public-python-tutorials

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

Language: Jupyter Notebook - Size: 96.7 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 124 - Forks: 90

RafeyIqbalRahman/Data-Imputation-Techniques

This repository demonstrates data imputation using Scikit-Learn's SimpleImputer, KNNImputer, and IterativeImputer.

Language: Python - Size: 8.79 KB - Last synced at: almost 2 years ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0

RafeyIqbalRahman/Dimensionality-Reduction-Techniques

This repository demonstrates reducing the dimensions of the dataset using Scikit-learn's Principal Component Analysis (PCA) and T-distributed Stochastic Neighbor Embedding (t-SNE).

Language: Python - Size: 3.91 KB - Last synced at: almost 2 years ago - Pushed at: almost 5 years ago - Stars: 0 - Forks: 0

Didilish/Asana-s-early-career-data-science-take-home-assessment

The project analyzed Asana user data to determine adoption rate and factors influencing adoption. After data cleaning, an adoption rate of 12% was calculated. Predictor variables were extracted and modeled using Random Forest and Decision Tree classifiers. Both models performed well, with Random Forest achieving 87% accuracy.

Language: Jupyter Notebook - Size: 546 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

NitishaS-812k/Music-Genre-Classifier

This repository contains the code for some models that classify music files into their specific genres

Language: Python - Size: 1.15 MB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 1 - Forks: 1

nafisalawalidris/Machine-Learning-with-Python

Machine Learning with Python final project: Apply ML algorithms to solve real-world problem. Hands-on experience in data preprocessing, model selection, evaluation. Showcase ML proficiency in Python.

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Ajaykumarrachuri/TitanicSurvival_prediction

This is the basic introductory project of machine learning for predicting the survivals category based on the data set available,which is implemented using different inbuilt models available in scikit learn

Language: R - Size: 53.7 KB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0

Marksman007577/Machine-Learning-and-Data-Science

Machine Learning and Data Science with Python

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Ghaithkrifa/jobs-analysis

Size: 2.93 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

cmurga95/oreilly_ml

Learning machine learning with python

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marinadunn/Foundations-of-Applied-ML

Notebooks for Foundation of Machine Learning (PHYS 243) Fall 2021 course at UCR

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Gowthamchandu307/Personal-Data-Science-Projects

This page contains some of my personal data science model projects. 📊📈📉👨‍💻

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souvikmajumder26/IEEE-ECG-Ensemble-XGBoost

👨‍💻 Developed AI Models - Ensemble of Random Forest & SVM and XGBoost classifiers to classify five types of Arrhythmic Heartbeats from ECG signals - published by IEEE.

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DorisKJ/life_expectancy

The data used in this work contains the life expectancy and probability of survival calculated for a given cohort from 1991 to 2001. This data is made available on the Canadian government website. Each dataset is described by income, education, ancestry, gender and residence type. Data: Life expectancy Survival probability

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npto04/random-forest-with-nlp 📦

Criação de modelo de classificação capaz de identificar documentos como petições iniciais com base de treinamento em dados do CRETA

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sotheanithsok/CECS-551-Collection 📦

Explore machine learning models and optimization techniques.

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UtsavMurarka/MXene-machine-learning

Classification of MXenes into metals and non-metals based on physical properties

Language: Jupyter Notebook - Size: 10.8 MB - Last synced at: over 2 years ago - Pushed at: almost 5 years ago - Stars: 4 - Forks: 1

Abdullahw72/Recognizing-Hand-written-digits-by-scikit-learn

Recognizing-Hand-written-digits-by-scikit-learn

Size: 30.3 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

digvijaytaunk/aps-fault-detection-with-deployment

Language: Jupyter Notebook - Size: 20.6 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

dblabs-mcgill-mila/machine_learning_with_sklearn

Explore and understand the Machine Learning concepts through the prism of sklearn, one notebook at a time.

Language: Jupyter Notebook - Size: 93.3 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

SupernovaSatsangi23/Modifying-Biomarker-Gene-Identification-For-Effective-Cancer-Categorization

A project that focuses on implementing a hybrid approach that modifies the identification of biomarker genes for better categorization of cancer. The methodology is a fusion of MRMR filter method for feature selection, steady state genetic algorithm and a MLP classifier.

Language: Python - Size: 6.84 KB - Last synced at: 4 months ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

Nadia-JSch/scatter-plot-iris-dataset

Permutations of sepal length, sepal width, petal length and petal width from the 3 classes of Iris on a scatter plot

Language: Python - Size: 156 KB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

RafaBragagd/Python-Code-Testing

Repositório de códigos de teste do Python feito por Rafael da Silva Braga

Size: 179 KB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

Anjali848/Solve-a-Mystery-in-History-Hamilton-or-Madison-

This code was submitted as part of the IST 707 (Applied Machine Learning) Homework assignment. In this homework assignment, you are going to use clustering methods to solve a mystery in history: who wrote the disputed essays, Hamilton or Madison?

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dassujan/Breast_Cancer_Detection

🎗️ I have completed this Machine learning Project successfully with 98.24% accuracy which is great for this project. Now, I'm ready to deploy our ML model in the healthcare project. To get more accuracy, I trained all supervised classification algorithms. After training all algorithms, I found that Logistic Regression, Random Forest and XGBoost classifiers are given high accuracy than remain but we have chosen XGBoost.

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marama09/Regression-Project-T5

Mobile Price Prediction

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breadrock1/ML-labs

Machine Learning. There is a suite of Machine Learning laboratory tasks.

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benjaminweymouth/machine_learning_Risky_Business

Machine Learning Examples: this repo is to show proficiency in building and evaluating several machine learning models to predict credit risk

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ignatius-mbugua/doctor-drug-prescription-system

A web app that assists doctors in prescribing right medicine to patients in order to avoid drug side effects

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PedroSiqueira1/PrevisaoPrecoImoveis

Projeto realizado para a matéria de Introdução ao Aprendizado de Máquina, onde foi feito um modelo regressor utilizando algoritmos de Machine Learning com a biblioteca Scikit-Learn em Python.

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