An automated machine learning toolkit.
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Updated
Jun 10, 2017 - Python
An automated machine learning toolkit.
Evaluations and experiments with time series models
House Price Prediction - Python, XGBoost, LightGBM
Python project that analyses CS:GO data
Linear regression analysis using two or more independent variables
Generate forecasts using several time series forecasting models
This repo contains various data science strategy and machine learning models to deal with structure as well as unstructured data. It contains module on feature-preprocessing, feature-engineering, machine-learning-models, bayesian-parameter-tuning, etc, built using libraries such as scikit-learn, keras, h2o, xgboost, lightgbm, catboost, etc.
output the results of multiple models with stars and export them as a excel/csv file.
🚀 Utility classes and functions for common data science libraries
A Time Series Analysis and Forecasting, using ARIMA and Prophet models, on a superstore dataset.
A practical example of time series decomposition
Various Exploratory Analysis of different datasets in python.
Automated the process of training time-series data with multiple Machine Learning and Stats Models to output the most accurate forecast result
McDonald versus Microsoft (Correlation coefficient and Spearman Rank Coefficient)
Forecasted traffic volume from 2016-2018 data to reduce traffic congestion and efficiently schedule road maintenance using time series models.
Algo trading strategy, entrance task to CMF, Quantitative Analytics program, 2021
pairs trading bot
How to make forecast with python ? I develop a software that allows to : - Make commercial forecasts from a history - Compare several forecasting methods - Display the results (forecasts and comparison)
An event analysis on the effect of large changes to circulating supply of Avalanche (AVA) token on abnormal returns.
Forecast Exchange rates between 2 given currencies using data from the past 2 months
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