xhluca

/* monochrome theme */
/* Colors */
/* Typography */
/* Borders */
/* Shadows */
/* Layout */
body {
  user-select: none;
  background: #000;
  font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Arial, sans-serif;

xhluca

xhluca

import base64
import xml
import plotly.graph_objects as go

def svg_to_fig(svg_bytes, title=None, plot_bgcolor='white', x_lock=False, y_lock=False):
    svg_enc = base64.b64encode(svg_bytes)
    svg = f'data:image/svg+xml;base64, {svg_enc.decode()}'
    
    # Get the width and height
    xml_tree = xml.etree.ElementTree.fromstring(svg_bytes.decode())

xhluca

import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import plotly.express as px

import pandas as pd

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

xhluca

# -*- coding: utf-8 -*-
"""
Speech Synthesis with Dash. This will only work with a Nvidia GPU.

Requirements (put them in requirements.txt):

apex
dash
numpy
scipy

xhluca

tensorflow
numpy
pandas
matplotlib
scikit-learn
jupyter
jupyterlab
seaborn

xhluca

# Short link: http://bit.ly/python-ml-bundle
# Usage (after creating a venv or conda env):
#     wget http://bit.ly/pip-ml-bundle
#     pip install -r pip-ml-bundle
#     rm pip-ml-bundle

# scientific
numpy
scipy

xhluca

import numpy as np
import tensorflow as tf

class TFRidge:
    def __init__(self, alpha=1.0, fit_intercept=True, normalize=False, solver='cholesky'):
        if solver != 'cholesky':
            raise ValueError('The only accepted solver is currently "cholesky"')
            
        self.alpha = alpha
        self.fit_intercept = fit_intercept

xhluca

%% md
# Scikit-Learn in the browser: Iris Classification

The goal of this notebook is to show how to use Scikit-learn directly in your browser, through pyodide. This particular example, we will train a simple classifier using the Iris data. Then, we will build an HTML GUI using Iodide, which will be used to interact with the classifier and perform predictions.

## Update your inputs
<div>
	Change Sepal length: 
	<input id="sepalLengthInput" type="range" step=0.1 min=4 max=8><br>
    Change Sepal width: 

xhluca

open Printf;;

type attribute =
  | Class of string
  | Href of string
  | Src of string
  | Style of string
  | Alt of string
  | Width of int
  | Height of int