Santiago Víquez santiviquez
santiviquez
/ drift_signals_model.py
Created
May 16, 2024 17:29
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| import numpy as np | |
| import nannyml as nml | |
| import pandas as pd | |
| class DriftSignalsModel: | |
| def __init__( | |
| self, | |
| y_pred_proba, | |
| y_pred, |
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| import numpy as np | |
| import pandas as pd | |
| import nannyml as nml | |
| import matplotlib.pyplot as plt | |
| reference_df = pd.DataFrame({'feature': np.random.normal(0, 0.1, 3000)}) | |
| analysis_df = pd.DataFrame({'feature': np.random.normal(0, 0.12, 3000)}) | |
| calc = nml.UnivariateDriftCalculator( |
santiviquez
/ min-char-rnn.py
Created
January 5, 2017 19:44
— forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
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| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |