thuwarakeshm

from django.urls import path

from views import sum_odd_numbers

urlpatterns = [
    path("sum_odd_numbers/<int:n>", sum_odd_numbers),
]

thuwarakeshm

import sys
from PyQt5.QtWidgets import QApplication, QWidget, QLabel
from PyQt5.QtGui import QIcon
from PyQt5.QtCore import pyqtSlot

def window():
   app = QApplication(sys.argv)
   widget = QWidget()

   textLabel = QLabel(widget)

thuwarakeshm

from aim.sdk.adapters.keras import AimCallback

model.fit(x_train, y_train, epochs=epochs, callbacks=[
    AimCallback(repo='/path/to/logs/dir', experiment='experiment_name')
])

thuwarakeshm

import tensorflow as tf

# create and train a keras neural network
classifier = tf.keras.models.Sequential([
    tf.keras.layers.Dense(units=1, input_shape=[1]),
    tf.keras.layers.Dense(units=28, activation='relu'),
    tf.keras.layers.Dense(units=1)
])
classifier.compile(optimizer='sgd', loss='mean_squared_error')
classifier.fit(x=[-1, 0, 1], y=[-3, -1, 1], epochs=5)

thuwarakeshm

# trainable property is available on model instances
model.trainable = False

# Also on individual layers
layer.trainable = False

thuwarakeshm

repos:
-   repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v4.0.1
    hooks:
    -   id: requirements-txt-fixer

thuwarakeshm

thuwarakeshm

import dash
import dash_core_components as dcc
import dash_html_components as html
from dash_html_components.Label import Label
from pandas.io.formats import style
import plotly.express as px
import pandas as pd
from dash.dependencies import Input, Output

app = dash.Dash(

thuwarakeshm

[context.secrets]

EMAIL_USERNAME = "<Your email id>"
EMAIL_PASSWORD = "<your email password>"

thuwarakeshm

@app.command()
def compare_with_target(input1: str, input2: str, target: str):

    # Read CSVs from arguments
    df1, df2 = pd.read_csv(input1), pd.read_csv(input2)

    # Generate a comparison report against the target variable
    report = sv.compare(df1, df2, target)

    # Render HTML report in your default browser