WDIS AI-ML Series: Module 1 Lesson 3: When to apply Rule Based Vs ML vs DL
I am sure when you complete the series, you will start looking at every problem through the lens of Machine Learning. This is what many companies or tech teams are doing. They are applying Machine learning for the sake of it. Some wise person rightly said, “When you have a hammer in your hand everything around you will appear as a nail”.
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Monetization: Price is right — Monetization strategy (Part II)
Monetization strategy should be an enabler of growth by maximizing the value captured and using that to create more value for existing users or to create value for new users.
Monetization: Price is right — Monetization strategy (Part III)
Pricing is an iterative process. Best way to get it right is to keep doing qualitative research, quantitative analysis, and roll out A/B testing to confirm your hypothesis.
A/B Testing : How to calculate sample size before launching your test
“How long are we planning to run the test? Do we have a significance yet?”. This is not an unusual situation. In fact all product managers run into this issue.
Metrics: ‘Satisficing’ Metric — Not all metrics need to be optimized
Not every metric should be maximized. Herbert Simon's 'satisficing' concept helps teams decide which metrics to optimize and which just need to be good enough.
A/B Testing: What to do when you do not have enough traffic on your site? (Part I)
A/B testing and decision making using statistical tools is as much a science as an art
A/B Testing: What to do when you do not have enough traffic on your site? (Part II)
There are a few others issues that product managers and analytics have to deal with, most important of them all is the opportunity cost of running an A/B test.
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