statsmodels
There are 684 repositories under statsmodels topic.
BayesWitnesses/m2cgen
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
mars-project/mars
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
dipanjanS/practical-machine-learning-with-python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
unslothai/hyperlearn
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
tirthajyoti/Stats-Maths-with-Python
General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
easystats/report
:scroll: :tada: Automated reporting of objects in R
jthomperoo/predictive-horizontal-pod-autoscaler
Horizontal Pod Autoscaler built with predictive abilities using statistical models
carlomazzaferro/scikit-hts
Hierarchical Time Series Forecasting with a familiar API
SoftwareAG/nyoka
Nyoka is a Python library that helps to export ML models into PMML (PMML 4.4.1 Standard).
ajitsingh98/Time-Series-Analysis-and-Forecasting-with-Python
Time Series Analysis and Forecasting in Python
Mogeng/IOHMM
Input Output Hidden Markov Model (IOHMM) in Python
heidelbergcement/hcrystalball
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
eigenfoo/tests-as-linear
Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.
30lm32/ml-time-series-analysis-on-sales-data
Time Series Decomposition techniques and random forest algorithm on sales data
thekioskman/mean_reversion_strategies
Here I go through the processing of prototyping a mean reversion trading strategy using statistical concepts, then test it in backtrader.
sayakpaul/A-B-testing-with-Machine-Learning
Implemented an A/B Testing solution with the help of machine learning
terence-lim/financial-data-science
Support financial data science workflow, manage large structured and unstructured data sets, and apply financial econometrics and machine learning
mrankitgupta/Statistics-for-Data-Science-using-Python
Sharing the solved Exercises & Project of Statistics for Data Science using Python course on Coursera by Ankit Gupta
terence-lim/financial-data-science-notebooks
Practical financial data science examples applying statistics, time series analysis, graph analytics, backtesting, machine learning, natural language processing, neural networks and LLMs
30lm32/ml-spam-sms-classification
Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification
JavierCastilloGuillen/Quantitative_Toolbox
On this repository you'll find tools used for Quantitative Analysis and some examples such: MonteCarlo Simulations, Linear Regression, General Data Visualiztions, Time-Series Analysis, etc.
nikhils10/Time-Series-Forecasting-Apple-Stock-Price-Using-SARIMA-Prophet
Time Series forecasting using Seasonal ARIMA & Prophet. Applied statistical tests like Augmented Dickey–Fuller test to check stationary of series. Checked ACF ,PACF plots to identify Moving average and Auto-regressive order of series. Transformed series to make it stationary.
santarabantoosoo/Data-Analysis-NanoDegree-2.0
Udacity FWD2.0 advanced data analysis nano degree connect sessions
midnightradio/tsa-tutorial
Material for the tutorial, "Time series analysis with pandas" at T-Academy
nirupamaprv/Analyze-AB-test-Results
E-Commerce Website A/B testing: Recommend which of two landing pages to keep based on A/B testing
amanjeetsahu/Time-Series-Analysis-and-Forecasting
End To End Tutorial on Time Series Analysis and Forcasting
MajorLift/volatility-modeling-python-datasci
Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."
esvs2202/Concrete-Compressive-Strength-Prediction
The aim of this project is to develop a solution using Data science and machine learning to predict the compressive strength of a concrete with respect to the its age and the quantity of ingredients used.
zeeshanmulla/Time-Series-Analysis-With-Python-TSA-
A Repo of Time-series analysis techniques. Holt-Winter methods, ACF/PACF, MA, AR, ARMA, ARIMA, SARIMA, SARIMAX, VAR, VARMA, RNN Keras, Facebook- Prophet etc.
rhatiro/Curso_EBAC-Profissao_Cientista_de_Dados
Exercícios do curso "Profissao: Cientista de Dados", sendo realizado pela EBAC - Escola Britânica de Artes Criativas e Tecnologia.
scailable/sclblpy
Python package for Scailable uploads
arunp77/Machine-Learning
Fundamentals & projects
msikorski93/Forecasting-Inflation-Rates-of-Poland
Recently inflation is a popular topic in Poland and is highest since 2001. Experts presume inflation in Poland should continue to rise, and by the end of 2021 it will be close to 8%. This notebook aims to develop a forecasting model for time series using Python.
Owinnie/Data-Science-Lab
Learning Data Science
ricardozacarias/ironhack-labs
The collection of exercises I did during Ironhack's Data Science bootcamp.
xxl4tomxu98/vector-autoregressive-model-wage-inflations
An econometrics vector autoregression model (VAR) for analysis of multivariate time series of macroeconomics phenomena. Python Jupyter notebook based model is presented here although other packages like R statistical programming language with R Studio could also be used.