2/n In business, I've made great regression models that have predicted how much sales we were going to make.
In fact, this helped me increase revenue from $3M to $15,000,000 per year at one of the companies I worked at.
BUT my models were NOT perfect.
In fact, this helped me increase revenue from $3M to $15,000,000 per year at one of the companies I worked at.
BUT my models were NOT perfect.
3/n In fact, I'd argue that the BIGGEST flops were due to over-confidence.
Believing my model was better than it actually was.
Here's what hurt me...
Believing my model was better than it actually was.
Here's what hurt me...
4/n 3 things that hurt me the most:
1. Anomalies (Outliers)
2. Skewed Data (Long tailed distributions)
3. Using error metrics based on in-sample data
This is where Bayesian can help.
1. Anomalies (Outliers)
2. Skewed Data (Long tailed distributions)
3. Using error metrics based on in-sample data
This is where Bayesian can help.
5/n I'd like to invite you to attend my FREE WORKSHOP on Bayesian, where I'm going over:
1. Why Bayesian is important to business
2. How to implement Bayesian for 90% of business problems
3. A case-study with code that shows you my strategies for analyzing bayesian models
1. Why Bayesian is important to business
2. How to implement Bayesian for 90% of business problems
3. A case-study with code that shows you my strategies for analyzing bayesian models
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