Valerio Maggio leriomaggio

#PyData Berlin Program, 2014

Friday, July 25

Time	Beginner/Intermediate Tutorial	Intermediate/Advanced Tutorial
12:00-12:45	Registration	Registration
-- --	-- -- -- --	-- -- -- --
12:45-14:05	Frank Kaufer (bakdata)	Bryan Van De Ven (Continuum Analytics)
	Python and Big Data Framework	Interactive Plots using Bokeh

import pandas as pd
import numpy as np

import pandas as pd
import numpy as np

Network Analysis Tutorial using Python & `networkx`

MSCX Ph.D. Summer School, Salina (ME) - Italy

Author: Valerio Maggio

PostDoc Data Scientist @ FBK/MPBA

import pandas as pd
import numpy as np
from IPython.display import HTML

Kubeflow Kale: from Jupyter Notebook to Complex Pipelines

Abstract

In this talk I will present a new solution to automatically scale Jupyter notebooks to complex and reproducibility pipelines based on Kubernetes and KubeFlow.

Description

Nowadays, most of the High Performance Computing (HPC) tasks are carried out in the Cloud, and this is as much

	#----------------------------------------------------------------------------------------
	# model.py
	#----------------------------------------------------------------------------------------
	from django.db import models
	from numpy.random import random_sample

	class CustomModel(models.Model):
	# Put your fields here

	def get_data(self):

	import umap
	import numpy as np
	import scipy as sp

	print('umap: ', umap.__version__)
	print('Numpy: ', np.__version__)
	print('Scipy: ', sp.__version__)

	# umap: 0.4.0
	# Numpy: 1.17.5

	"""Python/Numpy implementation of the Borda Count"""

	import numpy as np
	from nptyping import NDArray
	from typing import Tuple, Union, List, Any

	RankingsList = Union[NDArray[(Any, Any), np.int], List[List[int]]]
	Ranking = NDArray[(Any,), np.int]
	Counts = NDArray[(Any,), np.int]
	AveragePositions = NDArray[(Any,), np.float]

	from typing import Tuple, List, Optional, Union, NewType
	from typing import Protocol, runtime_checkable
	from abc import ABC, abstractmethod
	import pandas as pd
	try:
	import torch as t
	from torch import Tensor as Tensor
	except ImportError: # fallback to Numpy, if torch not available - this is just as a POP!
	import numpy as t
	from numpy import ndarray as Tensor