I use PyCharm for my python development and normally I use a virtual env but now I found poetry and it manages the dependencies in a better way than just having a pip requirements file.
I had issues loading correctly a poetry environment from docker compose into pycharm available environments.
This sometimes works, sometimes I just reload the entire environment.
Run your docker image of course.
| def add_noise(series, noise_level): | |
| return series * (1 + noise_level * np.random.randn(len(series))) | |
| def target_encode(trn_series=None, tst_series=None, target=None, k=1, f=1, noise_level=0): | |
| """ | |
| Encoding is computed like in the following paper by: | |
| Micci-Barreca, Daniele. "A preprocessing scheme for high-cardinality categorical attributes in classification and prediction problems." ACM SIGKDD Explorations Newsletter 3.1 (2001): 27-32. | |
| trn_series (pd.Series) : categorical feature in-sample |
| # -*- coding: utf8 -*- | |
| """Convex factorization machines | |
| Implements the solver by: Mathieu Blondel, Akinori Fujino, Naonori Ueda. | |
| "Convex factorization machines". Proc. of ECML-PKDD 2015 | |
| http://www.mblondel.org/publications/mblondel-ecmlpkdd2015.pdf | |
| """ | |
| # Author: Vlad Niculae <vlad@vene.ro> | |
| # License: Simplified BSD |
| """ Poisson-loss Factorization Machines with Numba | |
| Follows the vanilla FM model from: | |
| Steffen Rendle (2012): Factorization Machines with libFM. | |
| In: ACM Trans. Intell. Syst. Technol., 3(3), May. | |
| http://doi.acm.org/10.1145/2168752.2168771 | |
| See also: https://github.com/coreylynch/pyFM | |
| """ |
| japanese USB Keyboard: | |
| Interface 0 HID Report Descriptor Keyboard | |
| Usage Page (Generig Desktop) 0501 | |
| Usage (Keyboard) 0906 | |
| Collection (Application) A101 | |
| Usage Page (Keyboard/Keypad) 0507 | |
| Usage Minimum (Keyboard Left Control) 19E0 | |
| Usage Maximum (Keyboard Right GUI) 29E7 | |
| Logical Minimum (0) 1500 |
