text stringlengths 2.5k 6.39M | kind stringclasses 3
values |
|---|---|
# QDAE (Quantized Distribution Auto Encoder)
Basic question: Can we learn latent variable probability distribution?
Here we have single scalar value AE, so a very rudimentary problem.
x -> qd(h) -> h' -> x_bar
qd(h) is a quantized probability distribution of the latent variable h
h' is a weighted sum of qd(h) where ... | github_jupyter |
```
%matplotlib inline
import numpy as np
import time
import tensorflow as tf
from tensorflow import keras
import sys
sys.path.append("..")
import d2lzh_tensorflow2 as d2l
def get_data_ch7(): # 本函数已保存在d2lzh_tensorflow2包中方便以后使用
data = np.genfromtxt('../../data/airfoil_self_noise.dat', delimiter='\t')
data = (... | github_jupyter |
# note:
* [covariance matrix](http://docs.scipy.org/doc/numpy/reference/generated/numpy.cov.html)
* [multivariate_normal](http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.multivariate_normal.html)
* [seaborn bivariate kernel density estimate](https://stanford.edu/~mwaskom/software/seaborn/generated/sea... | github_jupyter |
# Lists
The data structures that we use most often in data science are:
* arrays, from `numpy`;
* data frames, from `pandas`.
There is another data structure for containing sequences of values
- the `list`.
You have already seen these in passing, when we created arrays. Now we cover them in more detail.
## Creati... | github_jupyter |
# Deep Neural Network for Image Classification: Application
When you finish this, you will have finished the last programming assignment of Week 4, and also the last programming assignment of this course!
You will use use the functions you'd implemented in the previous assignment to build a deep network, and apply i... | github_jupyter |
# Scraping Elsevier Metadata
This notebook is used for pulling metadata from articles via Scopus' literature search. It can technically be used to scrape abstracts from anywhere within Scopus' database, but we've specifically limited it to Elsevier journals as that is the only journal that we have access to the fullte... | github_jupyter |
```
import torch
from torch import nn
import torchvision
from torchvision.datasets import ImageFolder
from torchvision import transforms
from torch.utils.data import DataLoader
from pathlib import Path
from torchvision.models import resnet101
import sys
sys.path.append("..")
from video_classification.datasets import... | github_jupyter |
```
import os
os.chdir("..")
"""
Iterate over the PubMED articles that mention infecious diseases from the
disease ontology.
"""
import rdflib
from pylru import lrudecorator
import pubcrawler.article as pubcrawler
from annotator.keyword_annotator import KeywordAnnotator
from annotator.annotator import AnnoDoc
import re... | github_jupyter |
## Preliminaries
```
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import math
# Set ipython's max row display
pd.set_option('display.max_row', 1000)
# Set iPython's max column width to 50
pd.set_option('display.max_columns', 50)
```
## Create dataframe
```
df = pd.read_... | github_jupyter |
# About This Notebook
This notebook shows how to implement **Low-Rank Tensor Completion with Truncated Nuclear Norm minimization (LRTC-TNN)** on some real-world data sets. For an in-depth discussion of LRTC-TNN, please see our article [1].
<div class="alert alert-block alert-info">
<font color="black">
<b>[1]</b> Xin... | github_jupyter |
# Sequence Parameters
## *Sequence Type*: predefined sequence or waveform upload?
Many use cases require the freedom to define waveforms on a sample-basis. The `"Simple"` sequence type provided by the `zhinst-toolkit` allows for exactly that. If the *Simple* sequence is configured, the user can add waveforms to a que... | github_jupyter |
# ChainerRL Quickstart Guide
This is a quickstart guide for users who just want to try ChainerRL for the first time.
If you have not yet installed ChainerRL, run the command below to install it:
```
pip install chainerrl
```
If you have already installed ChainerRL, let's begin!
First, you need to import necessary m... | github_jupyter |
```
import os
import fnmatch
import pprint
import csv
from tqdm import tqdm
import numpy as np
import pandas as pd
import scipy.io as sio
from scipy.linalg import sqrtm
from analysis_clustering_helpers import get_cvfold_crossmodal_recon
cvsets_pth = './data/results/patchseq/reconstructions/'
metadata_file = './data/... | github_jupyter |
```
import tensorflow as tf
import tensorflow.contrib.layers as layers
from sklearn import datasets
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error
from sklearn.metrics import r2_score
imp... | github_jupyter |
# Portfolio Management with Amazon SageMaker RL
Portfolio management is the process of constant redistribution of a capital into a set of different financial assets. Given the historic prices of a list of stocks and current portfolio allocation, the goal is to maximize the return while restraining the risk. In this de... | github_jupyter |
<a href="https://colab.research.google.com/github/Katonokatono/Term-Deposit-Project/blob/Hypothesis-Testing/Term_Deposit_Hypothesis_Testing_Module1_Prj.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
#Import right libraries
import scipy.stats a... | github_jupyter |
```
%load_ext autoreload
%autoreload 2
from pathlib import Path
import sys
parent_path = str(Path().joinpath('..').resolve())
sys.path.append(parent_path)
from triple_agent.parsing.replay.get_parsed_replays import get_parsed_replays
from triple_agent.constants.paths import REPLAY_PICKLE_FOLDER
from triple_agent.classes... | github_jupyter |
# idftshift function
### Undoes the effects of iafftshift.
HS = dftshift(H).
HS: Image.
H: Image. DFT image with (0,0) in the center.
```
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import sys,os
ia898path = os.path.abspath('/etc/jupyterhub/ia898_1s2017/')... | github_jupyter |
# Breaking daily ranges
```
import pandas as pd
from datetime import timedelta, date
start_date = date(year=2021, month=9, day=1)
end_date = date(year=2021, month=11, day=1)
d1=pd.date_range(start_date, end_date, freq="W-FRI")
d1
d2=pd.date_range(start_date, end_date, freq="W-MON")
d2
ranges=[]
ranges.append((pd.Times... | github_jupyter |
# Midterm #2 Solution
```
import numpy as np
import pandas as pd
import statsmodels.api as sm
data = pd.read_excel('data/assetclass_data_monthly_2009.xlsx',index_col='Dates').loc['2012-01-31':]
exret = (data.subtract(data['Cash'],axis=0)).drop('Cash',axis=1)
exret
# 1.1.a
means = exret.mean()*12
display(means)
stds = ... | github_jupyter |
# Debug
```
# trying to find a potential bug --> but things look correct
# #!!!
# check that Protein_2_Function_and_Score_DOID_BTO_GOCC_STS_backtracked.txt has no redundant ENSP 2 function associations with different Scores
# ENSP = "9606.ENSP00000340944"
# funcName = "GO:0016020" # membrane
# # PTPN11 (ENSP000003409... | github_jupyter |
## Train a Scikit-Learn Model using SageMaker Script Mode
#### Bring Your Own Script (BYOS)
### Create Train Script
```
%%file train.py
from sklearn.neighbors import KNeighborsClassifier
from os.path import join
from io import BytesIO
import pandas as pd
import numpy as np
import argparse
import logging
import pickle... | github_jupyter |
# Stiffness in Initial Value Problems
Copyright (C) 2020 Andreas Kloeckner
<details>
<summary>MIT License</summary>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including ... | github_jupyter |
# Python Text Basics Assessment
Welcome to your assessment! Complete the tasks described in bold below by typing the relevant code in the cells.<br>
You can compare your answers to the Solutions notebook provided in this folder.
## f-Strings
#### 1. Print an f-string that displays `NLP stands for Natural Language Pro... | github_jupyter |
```
import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
from sqlalchemy import create_engine, inspect
engine = create_engine("sqlite:///../Resources/hawaii.sqlite")
#Data inspection
inspector = inspect(engine)
print(inspector.get_table_names())
columns = inspector.get_columns("measur... | github_jupyter |
# Interactome Construction and Analysis
Get data from local database and create the interactome
```
#Include libraries
import MySQLdb
import networkx as nx
from matplotlib import pylab as plt
import numpy as np
%matplotlib inline
def get_ppi(lcc):
'''
Main function to extract the PPI from our local database.
... | github_jupyter |
## What is Datashader?
**Datashader turns even the largest datasets into images, faithfully preserving the data's distribution.**
Datashader is an [open-source](https://github.com/bokeh/datashader/) Python 2 and 3 library for analyzing and visualizing large datasets. Specifically, Datashader is designed to "rasterize... | github_jupyter |
<h1>Understanding the Computation for Alpha and creating a function</h1>
```
import numpy as np
import matplotlib.pyplot as plt
from scipy import fft
import netCDF4 as nc
import cftime
import matplotlib.animation as animation
%matplotlib widget
# Get Data set from mission due to better notes on when in breaking
miss... | github_jupyter |
```
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writi... | github_jupyter |
```
import pandas as pd
import numpy as np
import missingno as msno
import matplotlib.pyplot as plt
```
### Load training data (from the starter notebook)
```
# this bit thanks to Brendon Hall
s3_train_csv = 's3://zarr-depot/wells/FORCE: Machine Predicted Lithology/train.csv'
data = pd.read_csv(s3_train_csv, sep=';')... | github_jupyter |
# QUESTIONS TO SUBJECT CLASSIFICATION
### Link to the Dataset: [Questions Data](https://www.kaggle.com/mrutyunjaybiswal/iitjee-neet-aims-students-questions-data)
### Importing Libraries
```
import pandas as pd
from sklearn import preprocessing
import nltk
nltk.download('stopwords') # download the st... | github_jupyter |
```
from matplotlib import pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
```
# Task 1
Данные:
```
urea = np.array([0, 3e-4, 5e-4, 1e-3, 2e-3, 3e-3, 5e-3])
mid_speed = np.array([0, 0.5, 0.77, 1.2, 1.57, 1.8, 1.9])
delta_speed = np.array([0, 0.05, 0.06, 0.08, 0.08, 0.09, 0.2])
```
График завис... | github_jupyter |
# Time Series Prediction
**Objectives**
1. Build a linear, DNN and CNN model in Keras.
2. Build a simple RNN model and a multi-layer RNN model in Keras.
In this lab we will with a linear, DNN and CNN model
Since the features of our model are sequential in nature, we'll next look at how to build various RNN model... | github_jupyter |
# Counterfactual explanations with one-hot encoded categorical variables
Real world machine learning applications often handle data with categorical variables. Explanation methods which rely on perturbations of the input features need to make sure those perturbations are meaningful and capture the underlying structure... | github_jupyter |
# {glue:text}`jupyter_github_org`
**Activity from {glue:}`jupyter_start` to {glue:}`jupyter_stop`**
```
from datetime import date
from dateutil.relativedelta import relativedelta
from myst_nb import glue
import seaborn as sns
import pandas as pd
import numpy as np
import altair as alt
from markdown import markdown
fr... | github_jupyter |
# XOR Prediction Neural Network
#### A simple neural network which will learn the XOR logic gate.
I will provide you with any links necessary so that you can read about the different aspects of this NN(Neural Network).
## Neural Network Info
#### All information regarding the neural network:
- Input Layer Units = 2... | github_jupyter |
# Word segmentation of Lao bibliographic data
Install packages not available in Google Colab.
```
#!pip install laonlp
#!pip install pyicu
#!pip install pythainlp
#!pip install botok
import sys
import regex as re
import pandas as pd
from laonlp.tokenize import word_tokenize as lao_wt
from pythainlp.tokenize import wo... | github_jupyter |
# Predict rating of review using BoardGameGeek Reviews dataset
**The goal of this project is to use the corpus of reviews present in this dataset, learn the reviews and their corresponding rating.**
**Once the model is trained using the review data, we ask the user to input a new review and predict the rating of that... | github_jupyter |
## 疫情数据分析和预测
疫情数据分析和预测是医学和流行病学应对大范围流行病时的重要判断手段，在医治隔离、预防响应、物资生产调配等抗疫措施上起到参考作用。
以下将通过已知模型尝试寻找合适拟合模型并对目前全球疫情发展作出一定程度的预测。
### 一、逻辑斯蒂模型（Logistic）
（1）模型描述：当一个物种迁入到一个新生态系统中后，其数量会发生变化。假设该物种的起始数量小于环境的最大容纳量，则数量会增长。该物种在此生态系统中有天敌、食物、空间等资源也不足（非理想环境），则增长函数满足逻辑斯谛方程，图像呈S形，此方程是描述在资源有限的条件下种群增长规律的一个最佳数学模型。
（2）一般疾病的传播是S型增长的过程，因为疾病传播的... | github_jupyter |
# Leave-K-Studies-Out Analysis
- This jupyter notebook is available on-line at:
- https://github.com/spisakt/RPN-signature/blob/master/notebooks/4_leave-k-studies-out.ipynb
- Input data for the notebook and non-standard code (PAINTeR library) is available in the repo:
- https://github.com/spisakt/RPN-signature
- Ra... | github_jupyter |
# Taylor Problem 16.14 version A
We'll plot at various times a wave $u(x,t)$ that is defined by its initial shape at $t=0$ from $x=0$ to $x=L$, using a Fourier sine series to write the result at a general time t:
$\begin{align}
u(x,t) = \sum_{n=1}^{\infty} B_n \sin(k_n x)\cos(\omega_n t)
\;,
\end{align}$
with $... | github_jupyter |
```
import ipywidgets as widgets
from ipywidgets import Accordion, HBox
from ipywidgets import FileUpload, Button
from ipyfilechooser import FileChooser
import json
import html
metadata={}
def _observe_elec_config(change):
print('_observe_elec_config')
metadata[ widget_elec_config.description] = widget_elec_co... | github_jupyter |
```
import numpy as np
from scipy.stats import norm
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
# Beginning in one dimension:
# mean = 0; Var = 1; N = 100
# scatter = np.random.normal(mean,np.sqrt(Var),N)
# scatter = np.sort(scatter)
t = [189.6071000099182, 191.2862000465393, 191.9226999282837... | github_jupyter |
# Lecture 06: Examples and overview
[Download on GitHub](https://github.com/NumEconCopenhagen/lectures-2021)
[<img src="https://mybinder.org/badge_logo.svg">](https://mybinder.org/v2/gh/NumEconCopenhagen/lectures-2021/master?urlpath=lab/tree/06/Examples_and_overview.ipynb)
1. [Recap](#Recap)
2. [The consumer problem... | github_jupyter |
# Computing the Bayesian Hilbert Transform-DRT
In this tutorial example, we will illustrate how the BHT-DRT model works for impedance data that is unbounded. The real experimental data was from the following article:
Wu et al. Dual-phase MoS2 as a high-performance sodium-ion battery anode. Journal of Materials Chemist... | github_jupyter |
# Document retrieval from wikipedia data
# Fire up GraphLab Create
```
import graphlab
```
# Load some text data - from wikipedia, pages on people
```
people = graphlab.SFrame('people_wiki.gl/')
```
Data contains: link to wikipedia article, name of person, text of article.
```
people.head()
len(people)
```
# Ex... | github_jupyter |
# Genotype data preprocessing
This section documents output from the genotype section (colored in light yellow) of command generator MWE and explained the purpose for each of the command. The file used in this page can be found at [here](https://drive.google.com/drive/folders/16ZUsciZHqCeeEWwZQR46Hvh5OtS8lFtA?usp=shari... | github_jupyter |
# Lesson 7 Class Exercises: Matplotlib
With these class exercises we learn a few new things. When new knowledge is introduced you'll see the icon shown on the right:
<span style="float:right; margin-left:10px; clear:both;"></span>
## Get Started
Import the Numpy, Pandas, Matplotli... | github_jupyter |
```
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from math import ceil
import sklearn.datasets
def prepare_swissroll_data(BATCH_SIZE=1000):
''' This is derived from https://github.com/lukovnikov/improved_wgan_training/blob/master/gan_toy.py
Copyright (c) 2017 Ishaan Gulrajani... | github_jupyter |
# Tutorial de Python
Tutorial de Python 3.6
## Tipos de dados
Em python você não precisa declarar as variaveis e nem especificar o tipo dela. Uma mesma variável também pode receber dados de tipos diferentes.
```
# Mesma variável recebendo tipos diferentes
var = 5
print(var)
var = "oi"
print(var)
var = 3.14
print... | github_jupyter |
# Make sentence evaluation sample dataset
We want to sanity check the accuracy of the [ArgumenText](https://api.argumentsearch.com/en/doc) API. One way to do this is spot checks on the results, and using those spot checks to estimate precision and recall.
**Precision**
Also known as "positive predictive value."
O... | github_jupyter |
```
import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn.decomposition import PCA
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
iris = datasets.load_iris()
X = iris.data #raw data
Y = iris.target #known groups (only for supervised analysis, I think)
target_names = iris.targ... | github_jupyter |
#Video Overlay
Add images, text, and audio to videos.
#License
Copyright 2020 Google LLC,
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless req... | github_jupyter |
# __DATA 5600: Introduction to Regression and Machine Learning for Analytics__
## __Notes on the Bayesian Beta-Bernoulli Conjugate Model__ <br>
Author: Tyler J. Brough <br>
Last Update: September 13, 2021 <br>
<br>
```
import numpy as np
from scipy import stats
import seaborn as sns
import matplotlib.pyplot as... | github_jupyter |
<a href="https://colab.research.google.com/github/predicthq/phq-data-science-docs/blob/master/academic-events/part_1_data_engineering.ipynb" target="_blank"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
##### Academic Events Data Science Guides
# Part 1: Data Engineerin... | github_jupyter |
# Using sci-analysis
From the python interpreter or in the first cell of a Jupyter notebook, type:
```
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import scipy.stats as st
from sci_analysis import analyze
```
This will tell python to import the sci-analysis function ``analyze()``.
> Note: A... | github_jupyter |
# Using `astropy.coordinates` to Match Catalogs and Plan Observations
## Authors
Erik Tollerud, Kelle Cruz
## Learning Goals
* TBD
## Keywords
coordinates, catalog matching, observational astronomy, astroquery
## Summary
In this tutorial, we will explore how the `astropy.coordinates` package and related astropy fun... | github_jupyter |
# Simple SPACE model example
Written by Charles M. Shobe to accompany the following publication:
Shobe, C.M., Tucker, G.E., and Barnhart, K.B.: The SPACE 1.0 model: A Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution, submitted to Geoscientific Model Development.
T... | github_jupyter |
# Classes
Variables, Lists, Dictionaries etc in python is a object. Without getting into the theory part of Object Oriented Programming, explanation of the concepts will be done along this tutorial.
A class is declared as follows
class class_name:
Functions
```
class FirstClass:
pass
```
**pass** in pytho... | github_jupyter |
<a href="https://colab.research.google.com/github/GabrielLourenco12/python_exercises/blob/main/Exercicios5.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
## Exercícios 5
Ler uma temperatura em graus Celsius e apresentá-la convertida em graus Fahre... | github_jupyter |
## Numpy
```
%matplotlib inline
%load_ext autoreload
%autoreload 2
import os
import sys
p = os.path.join(os.path.dirname('__file__'), '..')
sys.path.append(p)
from common import *
```
### Init
```
np.ones(10).astype(int)
np.zeros(10)
np.arange(1,10)
# Gaussian normal distribution
np.random.randn(2,2)
# Random unifor... | github_jupyter |
# Creating Python Virtual Environments with conda
- [Overview](#conda-virual-env-overview)
- [Setting Up a Virtual Environment Using conda](#setting-up-a-virtual-environment-using-conda)
- [Creating a conda Virtual Environment from a File](#creating-a-conda-environment-from-a-file)
- [Setting Up a RAPIDS conda Envir... | github_jupyter |
# Description
## This notebok provides set of commands to install Spark NLP for offline usage. It contains 4 sections:
1) Download all dependencies for Spark NLP
2) Download all dependencies for Spark NLP (enterprise/licensed)
3) Download all dependencies for Spark NLP OCR
4) Download all models/embeddings for offli... | github_jupyter |
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT License.
```
## Setup
To start, set up some functions to benchmark.
```
import time
import numpy as np
def test_fn_1():
good = np.random.poisson(20)
bad = np.random.poisson(100)
msec = np.... | github_jupyter |
```
%matplotlib inline
# %config InlineBackend.figure_format = 'svg'
%reload_ext autoreload
%autoreload 2
from __future__ import division
import sys
import os
sys.path.append('../')
from modules.basics import *
from sklearn.model_selection import train_test_split
from lumin.plotting.data_viewing import plot_rank_ord... | github_jupyter |
```
import numpy as np
import os
from skimage import io
from skimage import color, exposure, transform
from PIL import Image
import cv2
import matplotlib
import matplotlib.pyplot as plt
import sys
from shutil import copyfile
from skimage import data, img_as_float
from skimage import exposure
import shutil
import kera... | github_jupyter |
## Subplots with table and traces with different realtive position ##
```
from plotly.offline import download_plotlyjs, init_notebook_mode, iplot, plot
init_notebook_mode(connected=True)
import pandas as pd
import datetime
df=pd.read_excel('Mining-BTC-180.xls')
df.head()
df.columns
```
Convert each string in `df['D... | github_jupyter |
```
from collections import defaultdict
from sortedcontainers import SortedDict
import math
import pandas as pd
import numpy as np
from copy import copy
from pyqstrat.pq_utils import str2date
from pyqstrat.pq_types import ContractGroup
def calc_trade_pnl(open_qtys, open_prices, new_qtys, new_prices, multiplier):
''... | github_jupyter |
```
import os
import sys
module_path = os.path.abspath(os.path.join('..'))
sys.path.append(module_path)
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('whitegrid')
color = sns.color_palette()
%matplotlib inline
matplotlib.style.use('ggplot')
import time
import numpy as np
import... | github_jupyter |
# #2 Discovering Butterfree - Spark Functions and Window
Welcome to Discovering Butterfree tutorial series!
This is the second tutorial of this series: its goal is to cover spark functions and windows definition.
Before diving into the tutorial make sure you have a basic understanding of these main data concepts: fe... | github_jupyter |
# Calculate Coverage
You have a large region of interest. You need to identify an AOI for your study. One of the inputs to that decision is the coverage within the region. This notebook will walk you through that process.
In this notebook, we create the coverage map for PS Orthotiles collected in 2017 through August ... | github_jupyter |
<a href="https://colab.research.google.com/github/kalz2q/mycolabnotebooks/blob/master/arabic01.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# メモ
コードセルでは %%html とすると、html が書けるのでそれを利用すると、
文字に色をつけたり、大きくしたりができる。
それを利用してアラビア語の勉強をする、というアイデア。
うまく表示できた... | github_jupyter |
# Topic Modeling with DARIAH topics
We use this python library to do topic modeling on the AO3 corpus: https://dariah-de.github.io/Topics/
Issue: the library is designed to work with simple .txt files, while we have an R environment.
We need to convert the R environment into .txt files: this can be done directly v... | github_jupyter |
```
import urllib.request, json
with urllib.request.urlopen(
"https://api.steinhq.com/v1/storages/5e736c1db88d3d04ae0815b3/Raw_Data"
) as url:
data = json.loads(url.read().decode())
import pandas as pd
import re
from tqdm import tqdm
tqdm.pandas()
df = pd.DataFrame(data)
df["Notes"][30:35]
import spacy
nlp = s... | github_jupyter |
```
import sys
sys.path.append('..')
import os
import torch
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.preprocessing import LabelEncoder, MinMaxScaler, KBinsDiscretizer
from sklearn.impute import SimpleImputer
from sklearn.model_selection import cross_val_score
from sklearn.tree... | github_jupyter |
<h2>Fashion MNIST dataset in Keras library</h2>
## Imports
```
# - TensorFlow
import tensorflow as tf
# - Dataset
from tensorflow.keras.datasets import fashion_mnist
# - Helper libraries
import numpy as np
import pandas as pd
import time
from sklearn.metrics import confusion_matrix
from tensorflow.keras.utils import ... | github_jupyter |
# Demo: Using VGG with Keras
Below, you'll be able to check out the predictions from an ImageNet pre-trained VGG network with Keras.
### Load some example images
```
# Load our images first, and we'll check what we have
from glob import glob
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
# Visualiz... | github_jupyter |
<img src="../../images/qiskit-heading.gif" alt="Note: In order for images to show up in this jupyter notebook you need to select File => Trusted Notebook" width="500 px" align="left">
# Qiskit Aer: Simulators
The latest version of this notebook is available on https://github.com/Qiskit/qiskit-tutorials.
## Introduct... | github_jupyter |
# Example 3: Normalize data to MNI template
This example covers the normalization of data. Some people prefer to normalize the data during the preprocessing, just before smoothing. I prefer to do the 1st-level analysis completely in subject space and only normalize the contrasts for the 2nd-level analysis. But both ap... | github_jupyter |
## Practice: Mastering Kung-Fu and A2C
*This part is based on [Practical RL week08 practice](https://github.com/yandexdataschool/Practical_RL/tree/master/week08_pomdp). All rights belong to the original authors.*
```
import sys
if 'google.colab' in sys.modules:
!pip install scipy==1.0.1
!wget https://raw.gith... | github_jupyter |
```
import pandas as pd
import numpy as np
import datetime as dt
```
# **Task** **1**
```
#dummy data for task 1
df = pd.read_csv('data.csv')
df = df.drop([1693,1694],axis=0)
def date_difference(dataframe):
# Note***/// This function will do the job for any format of date values in column however i tried but c... | github_jupyter |
```
import digits
import tensorflow as tf
from time import time
import itertools as it
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, precision_score, f1_score, \
recall_score, classification_report, confusion_matrix
DATA_PATH = 'digits.csv'
LEAR... | github_jupyter |
# Creating structures in pyiron
This section gives a brief introduction about some of the tools available in pyiron to construct atomic structures.
For the sake of compatibility, our structure class is written to be compatible with the popular Atomistic Simulation Environment package ([ASE](https://wiki.fysik.dtu.dk/... | github_jupyter |
# Problem Set 2
See “Check Your Understanding” from [collections](../python_fundamentals/collections.ipynb) and [control flow](../python_fundamentals/control_flow.ipynb)
Note: unless stated otherwise, the timing of streams of payoffs is immediately at
time `0` where appropriate. For example, dividends $ \{d_1, d_2,... | github_jupyter |
# Collect all data
```
import struct
def get_byte_list(lbl_file_name, img_file_name):
'''
Returns a list of tuples,
each tuple contains a label and an image, both in bytes.
'''
tuples = []
with open(lbl_file_name, 'rb') as lbl_file, open(img_file_name, 'rb') as img_file:
magic_number... | github_jupyter |
```
from result_records import TFRecordLoader
ds = TFRecordLoader('memorization_results.tfrecords')
```
# Loading Data
> consists of 4063300 records
```
data = []
indicies = []
import numpy as np
from tqdm import tqdm
for i,(res,idx) in tqdm(enumerate(ds)):
res,idx = res.numpy(),idx.numpy()
if(not (np.isnan(... | github_jupyter |
```
## Import Libraies
import pandas as pd
%pylab inline
import numpy as np
import re
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
from math import sqrt
from sklearn.ensemble import RandomForestRegressor
from sklearn import preprocessing
import sklearn.model_selection as ms
import sklearn.me... | github_jupyter |
# Analysis of the loads acting on the building
## *Matteo Franzoi* - Academic Year 2019/2020
### matricola 166788 (triennale)
---
```
from engineering_notation import EngNumber
import math
import numpy as np
from decimal import Decimal
```
---
#### Snow Load
```
qsk = 1.39*(1+(788/728)**2);
print(qsk, 'kN/m^2\n~=')
... | github_jupyter |
# Notes (IFE - template)
### `{{cookiecutter.project_name}}::{{cookiecutter.session_id}}`
## 1. Usage
### 1.1. Jupyter
*You can fill inn the MarkDown cells (the cells without "numbering") by double-clicking them. Also remember, press `shift + enter` to execute a cell.*
A couple of useful links:
- [How to write ... | github_jupyter |
#Crime Data Collection Methodology
-Eric Ramon- Labs 21
Crime Data is available from several official sources. UCR (uniform crime report), NIBRS (National Incident-Based Reporting System) and SRS (Summary Reporting System) are reported on the FBI website.
The NIBRS is a newer standard that will be THE new standard by... | github_jupyter |
```
import matplotlib.pyplot as plt
import scipy.sparse as sp
import _pickle as pk
from helpers import load_data
from collaborativeFiltering import *
from cross_validation import k_fold_split, split_matrix
%matplotlib inline
%load_ext autoreload
%autoreload 2
def save(obj, path):
print('Saving at path : {}'.forma... | github_jupyter |
# Project 2: Transistors and Amplifiers
This project will introduce two basic techniques for using currents and voltages to control currents and voltages. Why would you want to do that? It turns out that many times the physical system we're working with is not *directly* compatable with the tools we have to control or... | github_jupyter |
<img width="200" src="https://mmlspark.blob.core.windows.net/graphics/Readme/cog_services_on_spark_2.svg" />
# Cognitive Services
[Azure Cognitive Services](https://azure.microsoft.com/en-us/services/cognitive-services/) are a suite of APIs, SDKs, and services available to help developers build intelligent applicati... | github_jupyter |
# Fitting the distribution of heights data
## Instructions
In this assessment you will write code to perform a steepest descent to fit a Gaussian model to the distribution of heights data that was first introduced in *Mathematics for Machine Learning: Linear Algebra*.
The algorithm is the same as you encountered in *... | github_jupyter |
# Mean Shift using Robust Scaler
This Code template is for the Cluster analysis using a simple Mean Shift(Centroid-Based Clustering using a flat kernel) Clustering algorithm along with feature scaling using Robust Scaler and includes 2D and 3D cluster visualization of the Clusters.
### Required Packages
```
!pip ins... | github_jupyter |
# This notebook explores the Energy Preserving Neural Network Idea!
-------------------------------------------------------------------------------------------------------------------
# Dataset used => MNIST
----------------------------------------------------------------------------------------------------------------... | github_jupyter |
### Load preprocessed data
Run the script that downloads and processes the MovieLens data.
Uncomment it to run the download & processing script.
```
# !python ../src/download.py
import numpy as np
from sklearn.model_selection import train_test_split
from torch import from_numpy
from torch.utils.data import DataLoader... | github_jupyter |
```
import numpy as np
import pandas as pd
import scipy as sp
import sklearn as sl
import seaborn as sns; sns.set()
import matplotlib as mpl
from sklearn.linear_model import LinearRegression
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import axes3d
from matplotlib import cm
%matplotlib inline
```
# ... | github_jupyter |
# Adding Object Detection Predictions to a Voxel51 Dataset
This notebook will add predictions from an object detection model to the samples in a Voxel51 Dataset.
Adapted from: https://voxel51.com/docs/fiftyone/recipes/model_inference.html
```
model_path = '/tf/model-export/lb-400images-efficientdet-d0-model/image_ten... | github_jupyter |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.