thtang / Business-Analytics-Using-Statistical-Modeling

Related projects ⓘ

Alternatives and complementary repositories for Business-Analytics-Using-Statistical-Modeling

• WillKoehrsen / mastering-large-datasets
  Work for Mastering Large Datasets with Python
  ☆18Updated last year
• Dataweekends / exploratory_data_analysis
  Few tutorials on pandas, matplotlib and seaborn
  ☆26Updated 8 years ago
• firmai / reddit-data-science-project-ideas
  Reddit Data Science Project Ideas
  ☆9Updated 4 years ago
• adeshpande3 / Music-Analysis
  Trying to apply deep learning to music analysis
  ☆12Updated 7 years ago
• CamDavidsonPilon / PyDataNY_2019_tutorial
  Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference
  ☆26Updated 5 years ago
• datacamp / datacamp_facebook_live_ny_resolution
  In this Facebook live code along session with Hugo Bowne-Anderson, you're going to check out Google trends data of keywords 'diet', 'gym'…
  ☆44Updated 6 years ago
• susanli2016 / Statistics-with-Python
  ☆26Updated 5 years ago
• fastai / sklearn-pandas
  Pandas integration with sklearn
  ☆21Updated 7 years ago
• pymc-learn / pymc-learn-book
  Book: Practical Probabilistic Machine Learning in Python
  ☆10Updated 3 years ago
• susanli2016 / Data-Analysis-with-Python
  Data analysis using numpy, pandas, matplotlib, seaborn, sqlite3, data wrangling
  ☆30Updated 5 years ago
• tirthajyoti / Symbolic-computation-Python
  Symbolic computation using SymPy and various applications
  ☆20Updated 6 years ago
• SimonOuellette35 / PyData-talk---Intro-to-PyMC3
  Companion code for my PyData talk: "Introduction to Probabilistic Programming with PyMC3"
  ☆13Updated 5 years ago
• exploripy / exploripy
  Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.
  ☆50Updated last year
• thomasjpfan / skconfig
  Experimental library for sampling and validating scikit-learn parameters
  ☆10Updated 5 years ago
• MaartenGr / feature-engineering
  Tips for Advanced Feature Engineering
  ☆52Updated 4 years ago
• mllite / sklearn_explain
  Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.
  ☆13Updated 3 years ago
• yingpublic / RMI-AI
  ☆17Updated 4 years ago
• elena-roff / overwatch-anova-svm
  Data Analysis and Machine Learning with Python: EDA with ECDF and ANOVA, Correlation and Regression analysis, Data standardisation and F…
  ☆10Updated 7 years ago
• pmservice / ai-openscale-tutorials
  Watson OpenScale tutorials including sample models, notebooks and applications
  ☆21Updated last year
• thismlguy / easyML
  A Python Package for data processing and building ML models, primarily based on pandas and sklearn libraries.
  ☆17Updated 5 years ago
• saturncloud / saturn-cloud-examples
  ☆19Updated 3 years ago
• yrbszhsh / Principles-of-Artificial-Intelligence-Learning-Algorithms
  My work on UCSD CSE 250B Principles of Artificial Intelligence: Learning Algorithms
  ☆13Updated 5 years ago
• brainy749 / CreditRiskPaper
  Codes for replication and implementation of techniques in our credit risk article
  ☆32Updated 5 years ago
• lopusz / pydata-berlin-2018
  ☆15Updated 6 years ago
• ManojKumarMaruthi / Time-Series-Forecasting
  Forecasting Monthly Sales of French Champagne - Perrin Freres
  ☆25Updated 5 years ago
• thismlguy / AJ_ML_Library
  This library is a wrapper for sklearn and works with data stored using Pandas module.
  ☆17Updated 8 years ago
• xcitech / insurance_ML_model
  Machine Learning based model to predict Insurance Pure Premium
  ☆12Updated 7 years ago
• JohnSnowLabs / spark-nlp-streamlit
  Spark NLP for Streamlit
  ☆15Updated 3 years ago
• PiotrTa / Mining-Massive-Datasets
  Data mining algorithms with Python
  ☆10Updated 5 years ago
• stef-aramp / Human_Resources_Analytics-Prediction
  Prediction of "left/stayed" employees using Decision Trees and more
  ☆10Updated 6 years ago