Time-series forecasting tecniques applied to the stock market
-
Updated
May 28, 2024 - Python
Time-series forecasting tecniques applied to the stock market
gradient-boosted regression and decision tree models on behavioural animal data
Data Science DRY OOP Umbrella Library
Input Output Hidden Markov Model (IOHMM) in Python
Exercícios do curso "Profissao: Cientista de Dados", sendo realizado pela EBAC - Escola Britânica de Artes Criativas e Tecnologia.
Stock price prediction models for alpaca.markets
Time Series Analysis of Airline Passenger Data, In this time series forecasting, taking data from kaggle site and applying ARIMA and SARIMAX model to evaluate seasional trends of passenger travelling via airlines.
A neural network model for predicting cryptocurrency prices using machine learning and time series analysis techniques.
Eco Visionaries is an application that aims to provide constant monitoring of AQI and WQI for a particular study area. It is a project developed for Kerala Govt. for SIH 2023
Dataiku DSS plugin to train Generalized Linear Models
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
Nyoka is a Python library that helps to export ML models into PMML (PMML 4.4.1 Standard).
A mosiac plot listing 200 animals from five different classes.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Python package for Scailable uploads
OpenClassrooms Data Analyst 2022-2023 - Projet 10
OpenClassrooms Data Analyst 2022-2023 - Projet 9
OpenClassrooms Data Analyst 2022-2023 - Projet 6
Intro to Machine Learning - Pattern Recognition for Fun and Profit
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
Add a description, image, and links to the statsmodels topic page so that developers can more easily learn about it.
To associate your repository with the statsmodels topic, visit your repo's landing page and select "manage topics."