oukhouya62 Goto Github PK

a-hidden-markov-model-hmm-for-predicting-bitcoin-prices-using-python

https://www.kaggle.com/code/hassanoukhouya/notebook199868180f

apprentissage

Science des Données Saison 3: Apprentissage Automatique / Statistique pour l'Intelligence Artificielle

armagarch

ARMA-GARCH

bitcoin_volatility_forecasting

GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management

bvcscrap

Python library to scrape financial data from Casablanca Stock Exchange(Bourse des Valeurs de Casablanca)

casabourselib

CasaBourseLib est un package Python que nous avons crée lors de nos travaux sur d'autres projets concernant la bourse de Casablanca, nous avons réalisé la difficulté d'obtenir des données à partir du site web officiel de la bourse. nous avons donc eu l'idée de créer un package qui permet d'obtenir des données d'actions cotée en bourse de manière instantanée et en quelques secondes, similairement au package de Yahoo Finance (yfinance).

cnn-lstm-attention

使用卷积神经网络-长短期记忆网络（bi-LSTM）-注意力机制对股票收盘价进行回归预测。The convolution neural network, short-term memory network and attention mechanism are used to predict the closing price.

data-scientist-roadmap

Toturial coming with "data science roadmap" graphe.

dow-jones-index-case-study

Machine Learning application in the financial field (Dow-Jones index case study)

draw_neural_network

Notebook python (Jupyter) permettant la génération de code LaTeX nécessaire au tracé d'un réseau de neurones

event_study

This repository introduces the event study model.

forecasting-real-gross-domestic-product--gdp--per-capita-using-arima-model

forecasting-real-gross-domestic-product-gdp-per-capita-using-arima-model

forecasting_air_pollution

Stacking a machine learning ensemble for multivariate time series forecasting, with the goal of predicting the one-period ahead PM 2.5 air pollution level, as published in Towards Data Science on Medium.com

github-slideshow

A robot powered training repository :robot:

how-to-predict-stock-prices-easily-demo

How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube

lstm_stock_prediction

Long short-term memory (LSTM) to predict Tesla stock prices using Keras

machine-learning-to-predict-energy-consumption

Building a machine learning model to predict energy consumption using LSTM (Long-Short Term Memory)

nba-player-performance-analysis-pca-hierarchical-clustering-and-k-means-clustering

In this project, we will analyze NBA player data using PCA and Clustering methods in R to evaluate player performance and help coaches make better decisions. Our results will be presented using graphs and tables to visualize the clusters' impact on the data.

pr-sentation_support_vector_machines-

pv_energy_forcasting_machine_learning

Multi-linear Retrogression/Random_Forest/SVR/KNN

quandl-r

This is Quandl's R Package

rossmann_tsa_forecasts

Time Series Analysis & Forecasting of Rossmann Sales with Python. EDA, TSA and seasonal decomposition, Forecasting with Prophet and XGboost modeling for regression.

seminar_10_06_2020

seriestemporelles

Projet serie temporelle M2 IRF ISFA 2017

skforecast

Time series forecasting with scikit-learn models

stock-market-forecasting

stock-price-prediction

Predicting stock price using historical data of a company, using Neural networks (LSTM).

sunflower-land

the-functionalities-of-the-gretl

The aim of this presentation is to propose an initiation, in terms applied to econometrics of time series or panel data, using a Gretl econometrics software with illustrative examples.