The practitioner's forecasting library
-
Updated
Jul 11, 2024 - Python
The practitioner's forecasting library
🔉 👦 👧Voice based gender recognition using Mel-frequency cepstrum coefficients (MFCC) and Gaussian mixture models (GMM)
A fast, robust library to check for offensive language in strings, dropdown replacement of "profanity-check".
🔉 👦 👧 👩 👨 Speaker identification using voice MFCCs and GMM
Recognition of the images with artificial intelligence includes train and tests based on Python.
Efficient sparse matrix implementation for various "Principal Component Analysis"
DMLLTDetectorPulseDiscriminator - A supervised machine learning approach for shape-sensitive detector pulse discrimination in lifetime spectroscopy applications
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.
Codes for "Parkinson’s Disease Diagnosis: Effect of Autoencoders to Extract Features from Vocal Characteristics"
This repository demonstrates data imputation using Scikit-Learn's SimpleImputer, KNNImputer, and IterativeImputer.
A Q&A based chatbot which queries the database to find responses for similar questions asked by the users
a python project that uses machine learning to estimate the weight of a fish.
24/01/2024 Jeyfrey J. Calero R. Aplicación de Redes Neuronales con scikit-learn streamlit, pandas, seaborn y matplolib
ML model deployment using docker, kubernetes; API deployment with FastAPI; and MLOps using MLFlow for water potability dataset
This repository contains the code for some models that classify music files into their specific genres
Employee Attrition Classification using Scikit-Learn
Flight Price Prediction Regression using Scikit-Learn
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.
Add a description, image, and links to the scikit-learn-python topic page so that developers can more easily learn about it.
To associate your repository with the scikit-learn-python topic, visit your repo's landing page and select "manage topics."