Alternatives and similar repositories for end-to-end-lead-scoring

Users that are interested in end-to-end-lead-scoring are comparing it to the libraries listed below

• BookletAI / lead-scoring-demo
  Building a end-to-end lead scoring machine learning example with Jupyter, Sagemaker, MLflow, and Booklet.ai.
  ☆23Updated 2 years ago
• Atreya22 / luigi_rosmann_sales
  Using Luigi to create a Machine Learning Pipeline using the Rossman Sales data from Kaggle
  ☆33Updated 9 years ago
• MarwaEshra / Create-Interactive-Dashboards-with-Streamlit-and-Python
  Create Interactive Dashboards with Streamlit and Python Coursera
  ☆10Updated 5 years ago
• WillKoehrsen / mastering-large-datasets
  Work for Mastering Large Datasets with Python
  ☆20Updated 2 years ago
• khuyentran1401 / prefect-docker
  Demo on how to use Prefect with Docker
  ☆27Updated 3 years ago
• tdpetrou / integrating-pandas-with-scikit-learn
  Tutorial covering a new workflow available going from pandas to scikit-learn
  ☆39Updated 2 years ago
• jalajthanaki / Customer_lifetime_value_analysis
  Customer life time analysis (CLV analysis). We are using Gamma-Gamma model to estimate average transaction value for each customer.
  ☆48Updated 7 years ago
• yoonkanglow / Causal-Impact-Analysis-Demo
  ☆26Updated 8 years ago
• AlexIoannides / ml-workflow-automation
  Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deploym…
  ☆64Updated 2 years ago
• carlomazzaferro / scikit-hts-examples
  Example usage of scikit-hts
  ☆57Updated 3 years ago
• asifahmed90 / pyspark-ML-in-Colab
  Pyspark in Google Colab: A simple machine learning (Linear Regression) model
  ☆38Updated 6 years ago
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆62Updated 2 years ago
• firmai / python-for-finance
  ☆14Updated 6 years ago
• juanitorduz / ml_prod_tutorial
  Explore tips and tricks to deploy machine learning models with Docker.
  ☆13Updated 2 years ago
• smazzanti / valicast
  Validation for forecasts
  ☆17Updated 2 years ago
• susanli2016 / Statistics-with-Python
  ☆26Updated 6 years ago
• StephenElston / DataScience350
  Material for UW Extension Data Science 350
  ☆19Updated 7 years ago
• alteryx / predict-household-poverty
  Predict the poverty of households in Costa Rica using automated feature engineering.
  ☆23Updated 5 years ago
• tirthajyoti / Synthetic-data-gen
  Various methods for generating synthetic data for data science and ML
  ☆80Updated 4 years ago
• niharikabalachandra / PropensityToConvert
  Propensity models make true predictions about a customer’s future behavior. With propensity models you can truly anticipate a customer's …
  ☆18Updated 6 years ago
• bodywork-ml / ml-pipeline-engineering
  Best practices for engineering ML pipelines.
  ☆36Updated 3 years ago
• zachrenwick / streamlit_forecasting_app
  This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your ow…
  ☆66Updated last year
• klostest / uplift_modeling
  ☆17Updated 5 years ago
• AutoViML / lazytransform
  Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.
  ☆65Updated 9 months ago
• yoonhwang / hands-on-data-science-for-marketing
  ☆26Updated 4 years ago
• BigDataRepublic / bdr-analytics-py
  Common data science and data engineering utilities to help us perform analytics. Our toolbox for data scientists, licensed under Apache-2…
  ☆30Updated 7 years ago
• algobeans / Time-Series-Forecasting
  Code to 1) scrap wikipedia page view counts, and to 2) conduct time series analysis with GAM
  ☆47Updated 8 years ago
• ColtAllen / btyd
  Buy Till You Die and Customer Lifetime Value statistical models in Python.
  ☆117Updated last year
• firmai / techniques
  Jupyter Notebook and Python business intelligence tools and techniques. [Raw upload]
  ☆85Updated 2 years ago
• DiegoUsaiUK / Propensity_Modelling
  Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
  ☆27Updated 2 years ago