statsmodels

There are 1 repository under statsmodels topic.

mars-project / mars
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
dask dataframe joblib lightgbm machine-learning numpy pandas python pytorch ray scikit-learn statsmodels tensor tensorflow xgboost
Language:Python 2420
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
machine-learning scikit-learn statistical-learning xgboost lightgbm java python c javascript go csharp php r dartlang statsmodels lightning haskell ruby rust
Language:Python 2103
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.
machine-learning deep-learning python classification clustering natural-language-processing computer-vision spacy nltk scikit-learn prophet time-series-analysis convolutional-neural-networks tensorflow keras statsmodels pandas jupyter notebook jupyter-notebook
Language:Jupyter Notebook 1928
danielhanchen / hyperlearn
Waiting hours for a future prediction is unacceptable. Hyperlearn makes AI and ML algorithms 50% faster, use 90% less memory and doesn't require you to use new hardware! ML Algorithms like PCA, Linear Regression, NMF are all faster!
machine-learning python statistics scikit-learn statsmodels pytorch deep-learning data-science data-analysis regression-models econometrics tensor neural-network gpu research optimization
Language:Jupyter Notebook 1247
tirthajyoti / Stats-Maths-with-Python
General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
analytics anova bayesian-statistics clustering data-science hypothesis-testing inferential-statistics machine-learning mathematical-programming mathematics matplotlib normal-distribution numerical-analysis numpy pandas probability python scipy statistics statsmodels
Language:Jupyter Notebook 591
report
easystats / report
:scroll: :tada: Automated reporting of objects in R
reporting r apa reports statsmodels bayesian models automated-report-generation easystats rstats manuscript describe report anovas scientific automatic hacktoberfest
Language:R 535
carlomazzaferro / scikit-hts
Hierarchical Time Series Forecasting with a familiar API
time-series machine-learning hierarchical-data fbprophet statsmodels exponential-smoothing time-series-analysis scikit-learn
Language:Python 191
SoftwareAG / nyoka
Nyoka is a Python library that helps to export ML models into PMML (PMML 4.4.1 Standard).
pmml python python-library nyoka pmml-exporter machine-learning scikit-learn xgboost lightgbm statsmodels
Language:Python 160
heidelbergcement / hcrystalball
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
sklearn fbprophet pmdarima sarimax time-series-forecasting time-series model-selection cross-validation statsmodels tbats sklearn-compatible sklearn-api sklearn-library transformer wrapper data-science sktime
Language:Python 139
Mogeng / IOHMM
Input Output Hidden Markov Model (IOHMM) in Python
python hidden-markov-model graphical-models sequence-to-sequence machine-learning linear-models sequence-labeling supervised-learning semi-supervised-learning unsupervised-learning time-series scikit-learn statsmodels
Language:Python 120
eigenfoo / tests-as-linear
Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.
linear-models python scipy statistical-tests statsmodels
Language:HTML 62
erdiolmezogullari / ml-time-series-analysis-on-sales-data
Time Series Decomposition techniques and random forest algorithm on sales data
time-series-analysis sales-forecasting sales regression-trees time-series-decomposition machinelearning datamining seaborn sklearn statsmodels
Language:Jupyter Notebook 34
sayakpaul / A-B-testing-with-Machine-Learning
Implemented an A/B Testing solution with the help of machine learning
python xgboost statsmodels sklearn
Language:Jupyter Notebook 30
nirupamaprv / Analyze-AB-test-Results
E-Commerce Website A/B testing: Recommend which of two landing pages to keep based on A/B testing
ab-testing hypothesis-testing logistic-regression p-value e-commerce landing-page statsmodels conversion-tracking
Language:HTML 23
midnightradio / tsa-tutorial
Material for the tutorial, "Time series analysis with pandas" at T-Academy
pandas time-series-analysis statsmodels
Language:Jupyter Notebook 21
santarabantoosoo / Data-Analysis-NanoDegree-2.0
Udacity FWD2.0 advanced data analysis nano degree connect sessions
sql statistical-analysis python statsmodels tableau
Language:Jupyter Notebook 21
scailable / sclblpy
Python package for Scailable uploads
deployment python machine-learning statsmodels
Language:Python 18
erdiolmezogullari / 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
word2vec gensim keras nlp machine-learning ml randomforest svm deep-learning classification naive-bayes sklearn pipeline gridsearchcv lstm-neural-networks spam-classification tf-idf statsmodels sms-classification sms
Language:Jupyter Notebook 16
m-clark / more-mixed-models-2019
Demonstration of alternatives to lme4
lme4 mgcv glmmtmb rstanarm brms mixed-models random-effects python statsmodels
Language:R 12
Roshanmahes / Python-for-Teachers
In this course, teachers with different experiences in programming get an overview of the most relevant packages and tools available for Python, and learn how they can be applied in teaching and research.
python scipy pandas scikit-learn matplotlib seaborn statsmodels plotly keras-tensorflow sagemath
Language:Jupyter Notebook 12
amanjeetsahu / Time-Series-Analysis-and-Forecasting
End To End Tutorial on Time Series Analysis and Forcasting
forecasting statsmodels pandas keras
Language:Jupyter Notebook 10
emunozlorenzo / MyCheatSheets
Awesome cheatsheets for Data Science
cheatsheet machine-learning machinelearning python sklearn scikit-learn time-series timeseries time statsmodels arima sarima sarimax prophet facebook-prophet series-temporales deep-learning deep-neural-networks
Language:Jupyter Notebook 8
ileanadatamania / Data-Science-Portfolio
Data Science Portfolio
kmeans-clustering nlp eda exploratory-data-analysis matplotlib seaborn sklearn wordcloud price-analysis statsmodels price-elasticity price-comparison ab-testing nltk poisson-distribution
Language:Jupyter Notebook 8
bhattbhavesh91 / linear-regression-assumptions
A small repository explaining how you can validate your linear regression model based on assumptions
linear-regression-assumptions linear-regression linear-regression-python statsmodels python ols-statsmodels video assumptions
Language:Jupyter Notebook 7
droconnel22 / Quantitive_Finance
A sample of Quantative Analysis on Markowitz Model, CAPM, Black Scholes, and VaR. Includes ML for stock price prediction.
modern-portfolio-theory capm black-scholes monte-carlo value-at-risk machine-learning-algorithms quantitative-finance knn-classification logistic-regression svc-svm scikit-learn random-walk arima-model arima-forecasting statsmodels
Language:Jupyter Notebook 7
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.
fundamental-analysis timeseries-forecasting arima-forecasting prophet python statsmodels stock-price-prediction valuation
Language:Jupyter Notebook 7
ricardozacarias / ironhack-labs
The collection of exercises I did during Ironhack's Data Science bootcamp.
pandas sql git tableau exploratory-data-analysis regex matplotlib seaborn api statistics probability-distribution scipy statsmodels scikit-learn numpy web-scraping goodness-of-fit hypothesis-testing tensorflow keras
Language:Jupyter Notebook 7
young2j / summary3
output the results of multiple models with stars and export them as a excel/csv file.
statsmodels summary-tables
Language:Python 7
ankishb / ml-toolbox
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.
data-science machine-learning feature-engineering h2o bayesian-optimization text-mining entity-embedding ensemble-model statsmodels
Language:Python 6
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.
arima sarimax autoregressive rnn-keras statsmodels facebook prophet varmax holt-winters-forecasting
Language:Jupyter Notebook 6
acforvs / Cointegrated-Pairs-Trading
Algo trading strategy, entrance task to CMF, Quantitative Analytics program, 2021
python3 statsmodels pandas
Language:Python 5
DiploDatos / AnalisisSeriesTemporales
Análisis de series temporales: optativa de #DiploDatos
forecasting statsmodels time-series-analysis
Language:Jupyter Notebook 5
kennethleungty / StatsAssume
Automating Assumption Checks for Regression Models (Work in Progress)
statsassume regression assumption-check assumptions linear-regression logistic-regression data-science machine-learning statistics statsmodels data-analytics python stats assumption-checks regression-models ml binary-logistic-regression multinomial-regression multilinear-regression multinomial-logistic-regression
Language:Python 5
leehanchung / btc_dash
Bitcoin Price Prediction Modeling and Dashboard
bitcoin dash dashboard forecasting plotly plotly-dash prediction-model statsmodels tensorflow
Language:Jupyter Notebook 5
terence-lim / financial-data-science
Financial and Investment Data Science - python code and examples for statistical and machine learning on structured and unstructured financial data sets
financial-data tick-data quant-factors text-mining data-science machine-learning network-science taq edgar pytorch spacy sklearn statsmodels
Language:Python 5
vaitybharati / Assignment-04-Simple-Linear-Regression-2
Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.
python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis r-square-values t-score model-testing distplot regression-plot
Language:Jupyter Notebook 5

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machine-learning data-science time-series clustering classification