Hassan OUKHOUYA's Projects
https://www.kaggle.com/code/hassanoukhouya/notebook199868180f
Science des Données Saison 3: Apprentissage Automatique / Statistique pour l'Intelligence Artificielle
ARMA-GARCH
GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management
Python library to scrape financial data from Casablanca Stock Exchange(Bourse des Valeurs de Casablanca)
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).
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.
Toturial coming with "data science roadmap" graphe.
Machine Learning application in the financial field (Dow-Jones index case study)
Notebook python (Jupyter) permettant la génération de code LaTeX nécessaire au tracé d'un réseau de neurones
This repository introduces the event study model.
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
A robot powered training repository :robot:
How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube
Long short-term memory (LSTM) to predict Tesla stock prices using Keras
Building a machine learning model to predict energy consumption using LSTM (Long-Short Term Memory)
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.
Multi-linear Retrogression/Random_Forest/SVR/KNN
This is Quandl's R Package
Time Series Analysis & Forecasting of Rossmann Sales with Python. EDA, TSA and seasonal decomposition, Forecasting with Prophet and XGboost modeling for regression.
Projet serie temporelle M2 IRF ISFA 2017
Time series forecasting with scikit-learn models
Predicting stock price using historical data of a company, using Neural networks (LSTM).
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.