tracek

import re
import numpy as np

with open('code-corp.log') as f:
    log = f.readlines()
    
latency = []
timeout = []

for idx, line in enumerate(log):

tracek

# For Khaned

FROM jupyter/base-notebook

USER $NB_UID

RUN pip install --yes ----no-cache-dir jupyter numpy matplotlib pandas pulp

COPY FooD_Kind.csv [destination]

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# The script illustartes stunning difference on my machine with processing of signal with multiprocessing and joblib. 
# The slowness of multiprocessing is likely caused by oversubscription 

import time
import numpy as np
import librosa
from joblib import Parallel, delayed
from functools import partial
from multiprocessing import Pool

tracek

Keybase proof

I hereby claim:

• I am tracek on github.
• I am tracek (https://keybase.io/tracek) on keybase.
• I have a public key ASAnakbg2gzt50cHIRePbtoR_SqQjqUgZGnoTMVhT6rpvgo

To claim this, I am signing this object:

tracek

# Use `LabelEncoder` to encode encode labels with value between 0 and n_classes-1.

import pandas as pd
from sklearn.preprocessing import LabelEncoder

df = pd.DataFrame({'UserName': ['Peter', 'Richard', 'Peter'], 'exam': [1,2,2], 'score': [70,80,60]})

le = LabelEncoder()
df['UserName'] = le.fit_transform(df['UserName'])

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def validate_against_metadata(met, paths):
    """
    Checks the list of images to ensure that a metadata entry exists for each one
    if this is not the case, remove that image from the upload list.
    Also check for blank values in the metadata fields, which will cause Property KeyErrors on GEE
    Behaviour at the moment is to stop the upload if either type of errors is found, to allow the user to edit the file.
    :param met - a dictionary of dictionaries containing the metadata entries:
    :param paths - a list of full filepaths:
    :return: updated list of full filepaths
    """