Hi, YT shown me your channel couple of days ago, but after watching just 1 video i instantly subscribed. Keep up yhe good work, your tutorials are well prepared, explained and simply interesting to watch. Best!
Very clear and clean model, would be nice make a video about how to know what kind of model choose on differents datasets. I think is a very difficult part of the process
how do i feed my individual employee data into the model to get their probability scores? example John has a 85% chance gonna leave the company, Mike has a 10% chance gonna leave the company and so on.
really enjoy your vidz , thank you for sharing knowledge. I understand the whole concept of get dummies and so on, but if i had a category which created 100's of columns I would have to write a specific code to input and match the column for new data suppose its ok for train / testing, however for entering new data it would be more challenging after it has been trained. I would loop through my columns matching the one which is relevant and inserting a 1 for example. would there be an easier way? a video on your way of doing it would be great.
Hi, YT shown me your channel couple of days ago, but after watching just 1 video i instantly subscribed. Keep up yhe good work, your tutorials are well prepared, explained and simply interesting to watch. Best!
Great video! I learned a lot, especially about the preprocessing steps (binary encoding and one hot encoding)
Great Video, after learning the theoretical concepts that kind of practical videos are must
Very clear, I'm french and anderstand everything :)
As always Great video! Thanks
Clear and useful. Hat-off to you.
Very clear and clean model, would be nice make a video about how to know what kind of model choose on differents datasets. I think is a very difficult part of the process
simple and nice!
Are you going to consider class 1 of your result in case of an imbalance dataset in predicting attrition?
Thanks a lot 😊
Great thanks!
how do i feed my individual employee data into the model to get their probability scores?
example John has a 85% chance gonna leave the company, Mike has a 10% chance gonna leave the company and so on.
Does this model say what combination of values gives you the highest/lowest chance of an individual attrition?
really enjoy your vidz , thank you for sharing knowledge.
I understand the whole concept of get dummies and so on, but if i had a category which created 100's of columns I would have to write a specific code to input and match the column for new data
suppose its ok for train / testing, however for entering new data it would be more challenging after it has been trained.
I would loop through my columns matching the one which is relevant and inserting a 1 for example.
would there be an easier way?
a video on your way of doing it would be great.
yes
Please share the code files and the links in the description as soon as possible for free 🙏 thank you so much brother ❤