Data Science - Part VI - Market Basket and Product Recommendation Engines

Derek Kane

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24 окт 2024

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Комментарии : 30

@greg.mars.victory 8 лет назад

Never saw more value added info in such concise way. Great thanks for your contribution!

@sarnjitbeesla302 8 лет назад

Excellent video. Complex ideas presented in a simple and easy to understand manner, look forward to watching the rest of this series.

@Shurdizzle 6 лет назад

Thanks for putting this video up Derek. It answered everything I wanted to know and gave me great real world examples. I'm pumped to check out the rest of the series.

@spicytuna08 9 месяцев назад

thank you so much. this video clarified so many questions i had. cannot thank you enough.

@helloras 8 лет назад

very useful and well explained.. look forward to go through few other tutorials as well..

@DerekKaneDataScience 8 лет назад

+Rakesh Sancheti Thank you for taking the time to watch the lecture and for the kind words. I appreciate this very much. Good luck and hope that you enjoy the other lectures too.

@rainegoin6168 6 лет назад

Hi! Could you please explain how did you get the 0.26 and 0.46? Hope you'll respond. Thanks

@thaumaturgeishere331 4 года назад

Well presented information and simple explanations of complex topics.

@rishichauhan4032 9 лет назад

Great job, Derek. Thanks for sharing!

@DerekKaneDataScience 8 лет назад

+Rishi Chauhan Thank you for your kind words and I am glad that you are finding some value here too. Carpe Diem

@Solehippy 7 лет назад

Thank you very much Derek, for this fundamental lesson.

@manjunathswamy2270 6 лет назад

Kush Gupta : Could you please help me understand how X U Y = 0.26 ???

@adityatirtatjahja3685 7 лет назад

Nice vid. Could you explain how do you come up with 0.26 in the confidence analysis and 0.46 in lit analysis?

@manjunathswamy2270 6 лет назад

How did you arrive at 0.26 of XUY??

@MasterofPlay7 4 года назад

you can also do a logistic regression for the last example given

@baldwin5709 4 года назад

Good explanation and examples

@harsha2bits 7 лет назад

It looks like the formula for Confidence and lift is wrong and so are the calculations (10:16). Please check I think it should be more like support(X ∩ Y)/ Support (X)

@91drox 6 лет назад

The formula is correct. X and Y don't have anything in common. (X can be {Milk, Butter} and Y can be {Cereal}). Here, we try to find the probability of X and Y occurring, when only X occurs. ( X -> Y).