Data Science library
Data Science can be more accessible even for beginners with the library of data science developed by DataSentics.
As data science includes repetitive tasks, it could seem not creative and routine scope. The situation gets more complicated when the beginners do not know which model they should use in each case. Consequently, more time and money are spent, leading to the low impact of the developments.
We created our own Data Science library, which works as guidance and enables beginner data analysts to train models correctly and quickly. This diminishes repetitiveness. It allows experienced users to skip a lot of repetitive code when dealing with standard modeling tasks. With Data Science library, you can even prepare your data for modeling such as, e.g., string indexing, one-hot encoding, columns assembling and scaling quickly.
Using our Data Science library helps to:
- Prepare data for modeling
- Select the best performing model based on cross-validation and hyperparameter selection.
- Compare model’s performance based on the most decisive metrics.