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https://github.com/firmai/business-analytics-and-mathematics-python-book
Advanced Business Analytics and Mathematics with Python (by @firmai)
https://github.com/firmai/business-analytics-and-mathematics-python-book
analytics business data-analysis data-science mathematics python
Last synced: about 2 months ago
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Advanced Business Analytics and Mathematics with Python (by @firmai)
- Host: GitHub
- URL: https://github.com/firmai/business-analytics-and-mathematics-python-book
- Owner: firmai
- Created: 2019-12-20T00:30:17.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-03-29T04:18:13.000Z (almost 4 years ago)
- Last Synced: 2024-05-19T07:11:41.582Z (8 months ago)
- Topics: analytics, business, data-analysis, data-science, mathematics, python
- Homepage:
- Size: 18.6 KB
- Stars: 89
- Watchers: 6
- Forks: 48
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-google-colab - Advanced Business Analytics and Mathematics in Python
README
# Advanced Business Analytics and Mathematics
##### Programmatic Google Colab Notebook Series (2018-2023)if you have some ideas, get in touch, [@dereknow](https://twitter.com/dereknow?lang=en)
--------------------
### Risk Engineering
#### Anomaly Detection
1. [Cross Sectional Multivariate Data](https://colab.research.google.com/drive/1rYcc05NI0MU5IReWgOADHr5R1J9kxnbW#scrollTo=whB7cEvdjC_M)
1. [Time Series Univariate](https://colab.research.google.com/drive/1rYcc05NI0MU5IReWgOADHr5R1J9kxnbW#scrollTo=5W0uuEqWMKBQ)
1. [Time Series Multi-variate Real Time](https://colab.research.google.com/drive/1rYcc05NI0MU5IReWgOADHr5R1J9kxnbW#scrollTo=yflg8pWYVoKp)
1. [Time Series Multi-variate](https://colab.research.google.com/drive/1rYcc05NI0MU5IReWgOADHr5R1J9kxnbW#scrollTo=yflg8pWYVoKp)
#### Predictive Maintenance
#### Financial Risk### Decision Science
#### Causal Analysis
1. [Causal Inference from Observational Data](https://drive.google.com/file/d/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2/view?usp=sharing)
1. [Causal Regressions](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=lPGhJMFbH5BJ)
1. [Uplift Modelling](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=WpXXNFbuIeWe)
1. [A/B Testing](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=593TzsMzVquj)
1. [Frequentist](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=2w8-8ZMPCzT0)
1. [Regression](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=hejyQQ-CS93j)
1. [Bayesian](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=NSBBCs8QfUIL)
1. [Causal Discovery](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=SWM4ZLp4he6i)#### Operations Research
1. Convex Optimisation
1. [Optimal Advertising Problem](https://colab.research.google.com/drive/1qyiIt3JQpmQnzilVwQGU_G3b0_Rc2Xck)
1. [Linear Programming](https://drive.google.com/file/d/1l56ZmbDKez15vlAt8neGEZHYIagciRsI/view?usp=sharing)
1. [Production Models with Linear Constraints](https://colab.research.google.com/drive/1l56ZmbDKez15vlAt8neGEZHYIagciRsI#scrollTo=SRXossXvecIC)
1. [Linear Blending Problems](https://colab.research.google.com/drive/1l56ZmbDKez15vlAt8neGEZHYIagciRsI#scrollTo=J8jKI-LbfvQl)
1. [Task Allocation Problems](https://colab.research.google.com/drive/1l56ZmbDKez15vlAt8neGEZHYIagciRsI#scrollTo=kV1GH1r13ix6)
1. [Assignment and Scheduling](https://colab.research.google.com/drive/1KSewu262VvzPjgfq1Mgpv3t13WtBuzS_#scrollTo=ALeiPMX3Dulx)
1. [Multiple Criteria Decisions](https://colab.research.google.com/drive/1qA_xbKQl8xZH_oqXwjywkI8spiD2vgE2#scrollTo=SWM4ZLp4he6i)
1. [TOPSIS](https://colab.research.google.com/drive/1KSewu262VvzPjgfq1Mgpv3t13WtBuzS_#scrollTo=cPLWJzdU9N3v)
1. [SKCriteria](https://colab.research.google.com/drive/1KSewu262VvzPjgfq1Mgpv3t13WtBuzS_#scrollTo=JRmRHMlxYLVD)
1. [Goal Programming](https://colab.research.google.com/drive/1KSewu262VvzPjgfq1Mgpv3t13WtBuzS_#scrollTo=ALeiPMX3Dulx)### Predictive Analytics
#### Employee
#### Customer### Segmentation Research
#### Clustering Problems