Topic: scikit-learn-python Goto Github

👇 Here are 116 public repositories matching this topic...

aadityasivas / scikit-learn
scikit-learn-python,A jupyter notebook which trains a model with scikit-learn
User: aadityasivas
Home Page: https://aadityasivas.github.io/scikit-learn/
scikit-learn-python jupyter-notebook

abhishekrs4 / ml_water_potability
scikit-learn-python,ML model deployment using docker, kubernetes; API deployment with FastAPI; and MLOps using MLFlow for water potability dataset
User: abhishekrs4
machine-learning machine-learning-model machine-learning-model-deployment machine-learning-model-management scikit-learn-python water-potability water-quality mlflow mlflow-model mlflow-sklearn

ajaykumarrachuri / titanicsurvival_prediction
scikit-learn-python,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
User: ajaykumarrachuri
scikit-learn-python machine-learning data-analysis rlanguage

ajayzinngg / simple-nltk-chatbot
scikit-learn-python,A Q&A based chatbot which queries the database to find responses for similar questions asked by the users
User: ajayzinngg
python3 nltk sqlite3 flask scikit-learn-python

akimcs / fish-weight-estimation
scikit-learn-python,a python project that uses machine learning to estimate the weight of a fish.
User: akimcs
csv-files linear-regression machine-learning matplotlib-python pandas-python scikit-learn-python

am-mirzanejad / heart-failure-prediction
scikit-learn-python,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.
User: am-mirzanejad
jupyter-notebook numpy pandas python randomforestclassifier scikit-learn-python svm machine-learning

ampa-ml-team / pd-classification
scikit-learn-python,Codes for "Parkinson’s Disease Diagnosis: Effect of Autoencoders to Extract Features from Vocal Characteristics"
Organization: ampa-ml-team
python3 keras-tensorflow scikit-learn-python mlp svm xgboost autoencoder parkinsons-disease uci-machine-learning ensemble-learning

architadesai / scikit-learn-projects
scikit-learn-python,Scikit-learn (sklearn) projects in form of Jupyter Notebooks
User: architadesai
sklearn sklearn-library sklearn-with-svm scikit-learn scikitlearn-machine-learning scikit-learn-python scikit-learn-api

aroojzahra908 / artifical-intelligence-and-machine-learning-
scikit-learn-python,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.
User: aroojzahra908
artificial-intelligence gradient-descent linear-regression machine-learning matplotlib numpy pandas scikit-learn-python

ashishpandey88 / nanda-devi-glacier-loss
scikit-learn-python,Feburary 7,2021 Ecological Disaster (Nanda Devi Glacier, IND: 7,108 m above sea level). Satellite image analysis using the methodology of image segmentation shows that the Glacier cover in Nanda Devi has substantially decreased over the last 4 decades. It has gone down from 43% in Year 1984 to 20% in Year 2022 (in relation to the captured area in image)
User: ashishpandey88
image image-processing image-segmentation spatial-analysis satellite-imagery climate-change climate-science climate-model glaciers glacier-modelling scikit-learn-python scikit-image

azevedontc / scikit-learnlibrary
scikit-learn-python,scikit-learn Library (sk-learn) / Biblioteca scikit-learn (sk-learn)
User: azevedontc
scikit-learn scikit-learn-python scikitlearn-machine-learning sk-learn sklearn sklearn-library

basemax / imagerecognitionai
scikit-learn-python,Recognition of the images with artificial intelligence includes train and tests based on Python.
User: basemax
recognition recognition-color recognition-py python matplotlib numpy opencv opencv-python pyparsing scikit-learn scikit-learn-python scipy sklearn artificial-intelligence artificial-intelligence-algorithms image-processing image-processing-library image-procesing image-processing-python

benjaminweymouth / machine_learning_risky_business
scikit-learn-python,Machine Learning Examples: this repo is to show proficiency in building and evaluating several machine learning models to predict credit risk
User: benjaminweymouth
machine-learning-algorithms credit credit-risk python3 jupyter-notebook scikit-learn scikitlearn-machine-learning scikit-learn-python

chandakakshat / digital-kisaan-portal
scikit-learn-python,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.
User: chandakakshat
machine-learning scikit-learn python aws-lambda aws-cli aws-s3 aws aws-cloudformation django bootstrap

dassujan / breast_cancer_detection
scikit-learn-python,🎗️ 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.
User: dassujan
data-analysis machine-learning matplotlib-pyplot numpy pandas scikit-learn-python seaborn-plots

dataprofessor / code
scikit-learn-python,Compilation of R and Python programming codes on the Data Professor YouTube channel.
User: dataprofessor
Home Page: http://youtube.com/dataprofessor
shiny exploratory-data-analysis python streamlit r datascience data-science machinelearning machine-learning python-data-science

dblabs-mcgill-mila / machine_learning_with_sklearn
scikit-learn-python,Explore and understand the Machine Learning concepts through the prism of sklearn, one notebook at a time.
Organization: dblabs-mcgill-mila
educational-project jupyter-notebook machine-learning mcgill-university mila python3 scikit-learn scikitlearn-machine-learning sklearn conda inria numpy pandas scikit-learn-python training-material visual

dnamay / ml-diabetes
scikit-learn-python,Early stage detection of Diabetes risk
User: dnamay
diabetes-prediction knn-classifier machine-learning python3 scikit-learn-python supervised-machine-learning

dpscience / dmlltdetectorpulsediscriminator
scikit-learn-python,DMLLTDetectorPulseDiscriminator - A supervised machine learning approach for shape-sensitive detector pulse discrimination in lifetime spectroscopy applications
User: dpscience
lifetime-spectroscopy machine-learning artificial-intelligence pulse-detection discriminator detector materials-science lifescience positron-lifetime-spectra fluorescence-microscopy-imaging

durveshbaharwal / enhanceing_gps_ml
scikit-learn-python,Enhancing GPS Positioning Accuracy Using Machine Learning
User: durveshbaharwal
dtr geopy gnss numpy pandas python rfr scikit-learn-python svr tensorflow

flo7up / relataly-public-python-tutorials
scikit-learn-python,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.
User: flo7up
Home Page: https://www.relataly.com
machine-learning deep-learning time-series-forecasting time-series-prediction recurrent-neural-networks stock-market-prediction twitter-bot churn-prediction keras-tensorflow scikit-learn-python

go-minseong / predicting-whether-your-mail-will-be-read
scikit-learn-python,predicting whether you read mail
User: go-minseong
machine-learning crwaling scikit-learn-python time-series-classification unbalanced-data

ignatius-mbugua / doctor-drug-prescription-system
scikit-learn-python,A web app that assists doctors in prescribing right medicine to patients in order to avoid drug side effects
User: ignatius-mbugua
python3 django2 decision-tree-classifier scikit-learn-python

isaccanedo / machine-learning-for-beginners
scikit-learn-python,:star2: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
User: isaccanedo
Home Page: https://microsoft.github.io/ML-For-Beginners/
data-science education machine-learning machine-learning-algorithms machinelearning machinelearning-python ml python r scikit-learn

jamshedali18 / introduction-to-machine-learning
scikit-learn-python,A Course from kaggle solved Exercises
User: jamshedali18
pandas-python scikit-learn-python

jeyjocar / redes-neuronales
scikit-learn-python,24/01/2024 Jeyfrey J. Calero R. Aplicación de Redes Neuronales con scikit-learn streamlit, pandas, seaborn y matplolib
User: jeyjocar
Home Page: https://redesneuronales.streamlit.app/
app artificial-intelligence programming-language python redes redes-neurais-artificiais streamlit scikit-learn scikit-learn-api scikit-learn-python

lawrence-krukrubo / machine_learning
scikit-learn-python,Machine learning is the sub-field of Computer Science, that gives Computers the ability to learn without being explicitly programmed (Arthur samuel, American pioneer in the field of Computer gaming and AI , coined the term Machine Learning in 1959, while at IBM )
User: lawrence-krukrubo
supervised-learning unsupervised-machine-learning linear-regression classification-algorithm clustering-algorithm knearest-neighbor-algorithm logistic-regression scikit-learn-python python tensorflow

lopez-christian / house-prices-linear-regression-project
scikit-learn-python,This repository includes my House Prices Multi-Variate Linear Regression-Flatiron School Module 2 Project. In this project I made use of the OSEMN methodology incorporating packages such as Pandas, NumPy, Matplotlib, Seaborn, and Scikit-Learn.
User: lopez-christian
Home Page: https://lopez-christian.github.io/2020-04-25-house-prices-linear-regression-project/
house-prices king-county scikit-learn sellers grade machine-learning linear-regression kaggle flatiron-school flatiron-school-project

machphy / sentiment-analysis
scikit-learn-python,analysis application developed with Streamlit, designed to facilitate the evaluation of review sentiments—positive or negative—by leveraging a pre-trained machine learning model. Users can input review text and instantly receive sentiment predictions through a streamlined, interactive web interface powered by Streamlit .
User: machphy
csv-files nltk pickle scikit-learn-python streamlit analysis data-science database python3 sentiment-analysis

microsoft / ml-for-beginners
scikit-learn-python,12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Organization: microsoft
Home Page: https://microsoft.github.io/ML-For-Beginners/
ml data-science machine-learning machine-learning-algorithms machinelearning python machinelearning-python scikit-learn scikit-learn-python r

mikekeith52 / scalecast
scikit-learn-python,The practitioner's forecasting library
User: mikekeith52
python time-series machine-learning data-science deep-learning forecasting keras scikit-learn mase msis

nafisalawalidris / machine-learning-with-python
scikit-learn-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.
User: nafisalawalidris
classification data-science hierarchical-clustering machine-learning regression scikit-learn-python scipy

najiaboo / textclassification
scikit-learn-python,Build custom vacab, Ham /Spam using tfidf , Movie review classification using TFIDF
User: najiaboo
scikit-learn-python scikit-learn-pipelines movie-review-classifier nlp-machine-learning ham-spam tf-idf countvectorizer nlp-preprocessing custom-vacabulary custom-vacabulary-builder

niitsuma / delayedsparse
scikit-learn-python,Efficient sparse matrix implementation for various "Principal Component Analysis"
User: niitsuma
correspondence-analysis principal-component-analysis sparse-matrix canonical-correlation-analysis scikit-learn-python python ca pca cca svd

nitishas-812k / music-genre-classifier
scikit-learn-python,This repository contains the code for some models that classify music files into their specific genres
User: nitishas-812k
musicgenre classifier neural-network keras-neural-networks fma-dataset scikit-learn-python

prajaktaag / poverty-prediction-and-analysis
scikit-learn-python,poverty prediction and analysis
User: prajaktaag
costa-rica data-science data-visualization deep-neural-networks feature-engineering kaggle-competition kears machine-learning poverty-prediction python3 scikit-learn-python sentimental-analysis tableau

rafeyiqbalrahman / data-imputation-techniques
scikit-learn-python,This repository demonstrates data imputation using Scikit-Learn's SimpleImputer, KNNImputer, and IterativeImputer.
User: rafeyiqbalrahman
datapreparation imputation imputation-methods preprocessing scikit-learn scikit-learn-python scikitlearn-machine-learning sklearn sklearn-library

reddyprasade / machine-learning-with-scikit-learn-python-3.x
scikit-learn-python,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).
User: reddyprasade
sklearn machine-learning machine-learning-algorithms regression python-3 python unsupervised-learning supervised-learning scikit-learn classification

respectknowledge / machine-learning-tutorials
scikit-learn-python,Machine Learning Tutorials
User: respectknowledge
numpy panadas scikit-learn-python keras-tensorflow

rifatsdas / satellite_machine_learning
scikit-learn-python,Unsupervised and supervised learning for satellite image classification
User: rifatsdas
satellite-data rasterio classifications kmeans-clustering support-vector-machines support-vector-classifier scikitlearn-machine-learning scikit-learn scikit-learn-python sentinels sentinel-2 sentinel-1 sentinel-3

robertlupas / sentisense
scikit-learn-python,An AI model built to understand the sentiments transmitted through a phrase.
User: robertlupas
ai ai-model ai-models python scikit-learn scikit-learn-python scikitlearn scikitlearn-machine-learning

shakthi011001 / sentimental-analysis-using-scikit-learn
scikit-learn-python,Sentiment analysis refers to analyzing an opinion or feelings about something using data like text or images, regarding almost anything. Sentiment analysis helps companies in their decision-making process. For instance, if public sentiment towards a product is not so good, a company may try to modify the product or stop the production. Although there are several known tasks related to sentiment analysis, in this project we will focus on the common binary problem of identifying the positive / negative sentiment that is expressed by a given text toward a specific topic
User: shakthi011001
Home Page: https://colab.research.google.com/drive/1t_5EZDGzrakP8MTggqy2nos1iWwD3bOM?usp=sharing
natural-language-processing scikit-learn-python sentiment-analysis

souvikmajumder26 / ieee-ecg-ensemble-xgboost
scikit-learn-python,👨‍💻 Developed AI Models - Ensemble of Random Forest & SVM and XGBoost classifiers to classify five types of Arrhythmic Heartbeats from ECG signals - published by IEEE.
User: souvikmajumder26
machine-learning data-science python python3 scikit-learn scikitlearn-machine-learning scikit-learn-python numpy pandas matplotlib

subhangisati / machine-learning
scikit-learn-python,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.
User: subhangisati
artificial-intelligence classification data-science decision-trees knn-classification knn-model linear-regression logistic-regression machine-learning machine-learning-algorithms python regression-algorithms regression-models scikit-learn-python scikitlearn-machine-learning svm-classifier

superkogito / voice-based-gender-recognition
scikit-learn-python,:sound: :boy: :girl:Voice based gender recognition using Mel-frequency cepstrum coefficients (MFCC) and Gaussian mixture models (GMM)
User: superkogito
gender-recognition gender-detection gender-classification gmm mfcc gender-recognition-by-voice voice mel-frequencies gaussian-mixture-models signal

superkogito / voice-based-speaker-identification
scikit-learn-python,:sound: :boy: :girl: :woman: :man: Speaker identification using voice MFCCs and GMM
User: superkogito
speaker-identification speaker-recognition gmm mfcc voice mel-frequency-cepstral-coefficients mel-frequencies gaussian-mixture-models signal machine-learning

tanvirnwu / ml-algorithms--scikit-learn--python
scikit-learn-python,This folder contains the basic algorithms of ML implemented with Python.
User: tanvirnwu
ai learning machine machine-learning ml scikit-learn scikit-learn-python scikitlearn-machine-learning scikitlearn

thamizhannal / insofe
scikit-learn-python,Works done at International School of Engineering
User: thamizhannal
stock-prediction stock-price-prediction stock-price-forecasting portfolio-optimization simulated-annealing monte-carlo-simulation scikitlearn-machine-learning scikit-learn-python

utsavmurarka / mxene-machine-learning
scikit-learn-python,Classification of MXenes into metals and non-metals based on physical properties
User: utsavmurarka
physics molecules atoms machine-learning deep-learning neural-network random-forest decision-trees logistic-regression knn-classifier