ols_regression
OLS regression with possibility of controlling for fixed effects and robust standard errors (by calosor)
Bayesian-Marketing-Mix-Modeling
The project analyses the impact of different marketing tactics on the sales of items. The problem is a multivariate-modeling problem as there are 3 different tactics of marketing. Since, the impact of marketing medium cannot be negative we will be using Bayesian model for regression. (by imnikhilanand)
ols_regression | Bayesian-Marketing-Mix-Modeling | |
---|---|---|
1 | 1 | |
0 | 4 | |
- | - | |
1.9 | 10.0 | |
about 1 year ago | almost 2 years ago | |
Python | Python | |
- | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ols_regression
Posts with mentions or reviews of ols_regression.
We have used some of these posts to build our list of alternatives
and similar projects.
-
OLS regression on Python with Fixed effects and robust std. errors
Here the link: https://github.com/calosor/ols_regression
Bayesian-Marketing-Mix-Modeling
Posts with mentions or reviews of Bayesian-Marketing-Mix-Modeling.
We have used some of these posts to build our list of alternatives
and similar projects.
-
How do you do Marketing Mix Modeling on a dataset when it contains other features in addition to the marketing spend columns? How do you handle those other, non-marketing channel, features?
I found out about MMM yesterday and I'm trying to understand how it works. So far, all the tutorials I have found and gone through make use of this advertising dataset, which contains only 5 columns - a time column, a sales figures column, and 3 marketing channel columns.
What are some alternatives?
When comparing ols_regression and Bayesian-Marketing-Mix-Modeling you can also consider the following projects:
twostage_regress - 2SLS IV regression with Python
scikit-learn - scikit-learn: machine learning in Python
pandas-profiling - Create HTML profiling reports from pandas DataFrame objects [Moved to: https://github.com/ydataai/pandas-profiling]