Pandas, numpy, scipy, sklearn, along with advanced techniques of their application. Basic integrations of python with external libraries like xgboost, tensorflow, pytorch along with data wrangling and some hyperparameter optimization methods will be also included. Jupyter notebook usage and tricks will be also given as an organic part of the course. At the end of module, everyone is expected to be ready to come up with a simple data wrangling system.
-
Notifications
You must be signed in to change notification settings - Fork 1
Pandas, numpy, scipy, sklearn, along with advanced techniques of their application. Basic integrations of python with external libraries like xgboost, tensorflow, pytorch along with data wrangling and some hyperparameter optimization methods will be also included. Jupyter notebook usage and tricks will be also given as an organic part of the cou…
Burntt/Python_for_Data_Science
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Pandas, numpy, scipy, sklearn, along with advanced techniques of their application. Basic integrations of python with external libraries like xgboost, tensorflow, pytorch along with data wrangling and some hyperparameter optimization methods will be also included. Jupyter notebook usage and tricks will be also given as an organic part of the cou…
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published