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---
_You are currently looking at **version 1.1** of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the [Jupyter Notebook FAQ](https://www.coursera.org/learn/python-data-analysis/resources/0dhYG) course resource._
---
# Assignment 2 - Pand... | github_jupyter |
```
pip install nltk
import nltk
import string
import re
texto_original = """Algoritmos inteligentes de aprendizados correndo supervisionados utilizam dados coletados. A partir dos dados coletados, um conjunto de característica é extraído. As características podem ser estruturais ou estatísticas. Correr correste corrid... | github_jupyter |
# Was Air Quality Affected in Countries or Regions Where COVID-19 was Most Prevalent?
**By: Arpit Jain, Maria Stella Vardanega, Tingting Cao, Christopher Chang, Mona Ma, Fusu Luo**
---
## Outline
#### I. Problem Definition & Data Source Description
1. Project Objectives
2. Data Source
3. Datase... | github_jupyter |
# Tensorflow Timeline Analysis on Model Zoo Benchmark between Intel optimized and stock Tensorflow
This jupyter notebook will help you evaluate performance benefits from Intel-optimized Tensorflow on the level of Tensorflow operations via several pre-trained models from Intel Model Zoo. The notebook will show users a... | github_jupyter |
<img src="../../img/logo_amds.png" alt="Logo" style="width: 128px;"/>
# AmsterdamUMCdb - Freely Accessible ICU Database
version 1.0.2 March 2020
Copyright © 2003-2020 Amsterdam UMC - Amsterdam Medical Data Science
# Vasopressors and inotropes
Shows medication for artificially increasing blood pressure (vasopr... | github_jupyter |
<a href="https://colab.research.google.com/github/EvenSol/NeqSim-Colab/blob/master/notebooks/process/masstransferMeOH.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
#@title Calculation of mass transfer and hydrate inhibition of a wet gas by inj... | 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 |
# Practical Examples of Interactive Visualizations in JupyterLab with Pixi.js and Jupyter Widgets
# PyData Berlin 2018 - 2018-07-08
# Jeremy Tuloup
# [@jtpio](https://twitter.com/jtpio)
# [github.com/jtpio](https://github.com/jtpio)
# [jtp.io](https://jtp.io)
# The Python Visualization Lan... | github_jupyter |
# Regressão linear
## **TOC:**
Na aula de hoje, vamos explorar os seguintes tópicos em Python:
- 1) [Introdução](#intro)
- 2) [Regressão linear simples](#reglinear)
- 3) [Regressão linear múltipla](#multireglinear)
- 4) [Tradeoff viés-variância](#tradeoff)
```
# importe as principais bibliotecas de análise de dado... | github_jupyter |
# Table of Contents
<p><div class="lev1 toc-item"><a href="#Lambda-calcul-implémenté-en-OCaml" data-toc-modified-id="Lambda-calcul-implémenté-en-OCaml-1"><span class="toc-item-num">1 </span>Lambda-calcul implémenté en OCaml</a></div><div class="lev2 toc-item"><a href="#Expressions" data-toc-modified-id="Exp... | github_jupyter |
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Dimensionality-Reduction" data-toc-modified-id="Dimensionality-Reduction-1"><span class="toc-item-num">1 </span>Dimensionality Reduction</a></span><ul class="toc-item"><li><span><a href="#The-Pro... | github_jupyter |
## 용어 정의
```
#가설설정
# A hypothesis test is a statistical method that uses sample data to evaluate a hypothesis about a population.
1. First, we state a hypothesis about a population. Usually the hypothesis concerns the value of a population parameter.
2. Before we select a sample, we use the hypothesis to predict the... | github_jupyter |
# 自然语言处理实战——命名实体识别
### 进入ModelArts
点击如下链接：https://www.huaweicloud.com/product/modelarts.html ， 进入ModelArts主页。点击“立即使用”按钮，输入用户名和密码登录，进入ModelArts使用页面。
### 创建ModelArts notebook
下面，我们在ModelArts中创建一个notebook开发环境，ModelArts notebook提供网页版的Python开发环境，可以方便的编写、运行代码，并查看运行结果。
第一步：在ModelArts服务主界面依次点击“开发环境”、“创建”
1. [Set-up](#Set-up)
1. [The corpus](#The-corpus)
1. [Corpus reader](#Corpus-reader)
1. [ColorsCorpusExample instances](#ColorsCorpusExample-instances)
1. [... | github_jupyter |
Uploading an image with graphical annotations stored in a CSV file
======================
We'll be using standard python tools to parse CSV and create an XML document describing cell nuclei for BisQue
Make sure you have bisque api installed:
> pip install bisque-api
```
import os
import csv
from datetime import date... | github_jupyter |
Copyright © 2017-2021 ABBYY Production LLC
```
#@title
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... | github_jupyter |
```
lat = 40.229730557967
lon = -74.002934930983
profile = [
{
"key": "natural",
"value": "beach",
"distance_within": 15,
"type": "bicycle",
"weight": 20
},
{
"key": "name",
"value": "Newark Penn Station",
"distance_within": 60,
"type"... | github_jupyter |
## Dependencies
```
import os
import sys
import cv2
import shutil
import random
import warnings
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from tensorflow import set_random_seed
from sklearn.utils import class_weight
from sklearn.model_selection import train_test_split... | github_jupyter |
# Exp 43 analysis
See `./informercial/Makefile` for experimental
details.
```
import os
import numpy as np
from IPython.display import Image
import matplotlib
import matplotlib.pyplot as plt`
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import seaborn as sns
sns.set_style('ticks')
matplotlib.... | github_jupyter |
```
!pip install wandb
!wandb login
from collections import deque
import random
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.transforms as transforms
import gym
import wandb
class Actor(nn.Module):
def __init__(self, num_actions):
super().__ini... | github_jupyter |
## Introduction
If you've had any experience with the python scientific stack, you've probably come into contact with, or at least heard of, the [pandas][1] data analysis library. Before the introduction of pandas, if you were to ask anyone what language to learn as a budding data scientist, most would've likely said ... | github_jupyter |
```
# Load WSC dataset
import xml.etree.ElementTree as etree
import json
import numpy as np
import logging
import numpy
import os
def softmax(x):
return np.exp(x)/sum(np.exp(x))
tree = etree.parse('WSCollection.xml')
root = tree.getroot()
original_problems = root.getchildren()
problems = list()
for original_pr... | github_jupyter |
## Analyze A/B Test Results
You may either submit your notebook through the workspace here, or you may work from your local machine and submit through the next page. Either way assure that your code passes the project [RUBRIC](https://review.udacity.com/#!/projects/37e27304-ad47-4eb0-a1ab-8c12f60e43d0/rubric). **Ple... | github_jupyter |
## Random Forest Classification
### Random Forest
#### The fundamental idea behind a random forest is to combine many decision trees into a single model. Individually, predictions made by decision trees (or humans) may not be accurate, but combined together, the predictions will be closer to the mark on average.
###... | github_jupyter |
<a href="https://colab.research.google.com/github/thingumajig/colab-experiments/blob/master/RetinaNet_Video_Object_Detection.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# .init
## setup keras-retinanet
```
!git clone https://github.com/fizyr/k... | github_jupyter |
# Objective
* 20190815:
* Given stock returns for the last N days, we do prediction for the next N+H days, where H is the forecast horizon
* We use double exponential smoothing to predict
```
%matplotlib inline
import math
import matplotlib
import numpy as np
import pandas as pd
import seaborn as sns
import t... | github_jupyter |
# 스파크를 이용한 기본 지표 생성 예제
> 기본 지표를 생성하는 데에 있어, 정해진 틀을 그대로 따라하기 보다, 가장 직관적인 방법을 지속적으로 개선하는 과정을 설명하기 위한 예제입니다.
첫 번째 예제인 만큼 지표의 복잡도를 줄이기 위해 해당 서비스를 오픈 일자는 2020/10/25 이며, 지표를 집계하는 시점은 2020/10/26 일 입니다
* 원본 데이터를 그대로 읽는 방법
* dataframe api 를 이용하는 방법
* spark.sql 을 이용하는 방법
* 기본 지표 (DAU, PU)를 추출하는 예제 실습
* 날짜에 대한 필터를 넣는 방법
* 날짜에 대... | github_jupyter |
## AI for Medicine Course 1 Week 1 lecture exercises
<a name="counting-labels"></a>
# Counting labels
As you saw in the lecture videos, one way to avoid having class imbalance impact the loss function is to weight the losses differently. To choose the weights, you first need to calculate the class frequencies.
For ... | github_jupyter |
```
import psycopg2
import pandas as pd
import pandas.io.sql as pd_sql
import numpy as np
import matplotlib.pyplot as plt
def connectDB(DB):
# connect to the PostgreSQL server
return psycopg2.connect(
database=DB,
user="postgres",
password="Georgetown16",
host="database-1.c5vispb... | github_jupyter |
# Introduction à Python
> présentée par Loïc Messal
## Introduction aux flux de contrôles
### Les tests
Ils permettent d'exécuter des déclarations sous certaines conditions.
```
age = 17
if age < 18:
print("Mineur") # executé si et seulement si la condition est vraie
age = 19
if age < 18:
print("Mineur") ... | github_jupyter |
# Introduction
Linear Regression is one of the most famous and widely used machine learning algorithms out there. It assumes that the target variable can be explained as a linear combination of the input features. What does this mean? It means that the target can be viewed as a weighted sum of each feature. Let’s use ... | github_jupyter |
######The Iris flower data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems. The dataset consists of 50 samples from each of three species of Iris (Iris Setosa, Iris virginica, and Iris versicolor).... | github_jupyter |
```
%load_ext autoreload
%autoreload 2
import pathlib
import IPython.display
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import scipy.interpolate
import scipy.signal
import pymedphys
import pymedphys._wlutz.iview
indexed_dir = pathlib.Path(r'S:\DataExchange\iViewDB_decoded\indexed')
movie... | github_jupyter |
# Flopy MODFLOW Boundary Conditions
Flopy has a new way to enter boundary conditions for some MODFLOW packages. These changes are substantial. Boundary conditions can now be entered as a list of boundaries, as a numpy recarray, or as a dictionary. These different styles are described in this notebook.
Flopy also n... | github_jupyter |
# T81-558: Applications of Deep Neural Networks
* Instructor: [Jeff Heaton](https://sites.wustl.edu/jeffheaton/), School of Engineering and Applied Science, [Washington University in St. Louis](https://engineering.wustl.edu/Programs/Pages/default.aspx)
* For more information visit the [class website](https://sites.wust... | github_jupyter |
```
import statistics
import pprint
import pandas as pd
import numpy as np
from random import uniform
from tslearn.utils import to_time_series_dataset
from tslearn.metrics import dtw#, gak
import plotly.express as px
import scipy.stats as st
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import s... | github_jupyter |
# Reading and writing fields
There are two main file formats to which a `discretisedfield.Field` object can be saved:
- [VTK](https://vtk.org/) for visualisation using e.g., [ParaView](https://www.paraview.org/) or [Mayavi](https://docs.enthought.com/mayavi/mayavi/)
- OOMMF [Vector Field File Format (OVF)](https://ma... | github_jupyter |
<img align="center" style="max-width: 1000px" src="banner.png">
<img align="right" style="max-width: 200px; height: auto" src="hsg_logo.png">
## Lab 05 - "Convolutional Neural Networks (CNNs)" Assignments
GSERM'21 course "Deep Learning: Fundamentals and Applications", University of St. Gallen
In the last lab we le... | github_jupyter |
# Colab FAQ
For some basic overview and features offered in Colab notebooks, check out: [Overview of Colaboratory Features](https://colab.research.google.com/notebooks/basic_features_overview.ipynb)
You need to use the colab GPU for this assignmentby selecting:
> **Runtime** → **Change runtime type** → **Har... | github_jupyter |
```
import numpy as np
%%html
<style>
.pquote {
text-align: left;
margin: 40px 0 40px auto;
width: 70%;
font-size: 1.5em;
font-style: italic;
display: block;
line-height: 1.3em;
color: #5a75a7;
font-weight: 600;
border-left: 5px solid rgba(90, 117, 167, .1);
padding-left: 6px;
}
.notes {
font-st... | github_jupyter |
```
# Copyright 2021 NVIDIA Corporation. All Rights Reserved.
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | github_jupyter |
<table class="ee-notebook-buttons" align="left">
<td><a target="_blank" href="https://github.com/giswqs/earthengine-py-notebooks/tree/master/Datasets/Vectors/landsat_wrs2_grid.ipynb"><img width=32px src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" /> View source on GitHub</a></td>
<td><a target="_b... | github_jupyter |
```
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
# set random seed for comparing the two result calculations
tf.set_random_seed(1)
# this is data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
# hyperparameters
lr = 0.001
training_iters = 100000
batch_size = 128
n... | github_jupyter |
This notebook shows:
* How to launch the [**StarGANv1**](https://arxiv.org/abs/1711.09020) model for inference
* Example of results for both
* attrubutes **detection**
* new face **generation** with desired attributes
Here I use [**PyTorch** implementation](https://github.com/yunjey/stargan) of the StarGANv1 m... | github_jupyter |
```
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.metrics import accuracy_score, confusion_matrix
from sklearn.tree import export_text
```
This example uses the [Universal Bank](https://www.kaggle.com/sriharipramod/ba... | github_jupyter |
# Finetuning of the pretrained Japanese BERT model
Finetune the pretrained model to solve multi-class classification problems.
This notebook requires the following objects:
- trained sentencepiece model (model and vocab files)
- pretraiend Japanese BERT model
Dataset is livedoor ニュースコーパス in https://www.rondhuit.com... | github_jupyter |
```
import json
import math
import numpy as np
import openrtdynamics2.lang as dy
import openrtdynamics2.targets as tg
from vehicle_lib.vehicle_lib import *
# load track data
with open("track_data/simple_track.json", "r") as read_file:
track_data = json.load(read_file)
#
# Demo: a vehicle controlled to follow a gi... | github_jupyter |
##### Copyright 2019 The TensorFlow Authors.
```
#@title 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 ... | github_jupyter |
# Tabular Datasets
As we have already discovered, Elements are simple wrappers around your data that provide a semantically meaningful representation. HoloViews can work with a wide variety of data types, but many of them can be categorized as either:
* **Tabular:** Tables of flat columns, or
* **Gridded:** Arr... | github_jupyter |
# Summarize titers and sequences by date
Create a single histogram on the same scale for number of titer measurements and number of genomic sequences per year to show the relative contribution of each data source.
```
import Bio
import Bio.SeqIO
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
imp... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import wikipedia
import xml.etree.ElementTree as ET
import re
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA
from sklearn.model_selection import cross_val_score
import xgboost as xgb
from sklearn.metrics import r2_score
... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import yaml
from pathlib import Path
from collections import defaultdict
from pandas.api.types import CategoricalDtype
EXPERIMENTS_PATH = Path.home() / "ba" / "experiments"
benchmarks_paths = list((EXPERIMENTS_PATH / "C4P4").glob("lb.*/*.benchma... | github_jupyter |
### Road Following - Live demo (TensorRT) with collision avoidance
### Added collision avoidance ResNet18 TRT
### threshold between free and blocked is the controller - action: just a pause as long the object is in front or by time
### increase in speed_gain requires some small increase in steer_gain (once a slider is... | github_jupyter |
```
# %load hovorka.py
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint
def model(x, t, t_offset=None):
w = 100
ka1 = 0.006 #
ka2 = 0.06 #
ka3 = 0.03 #
kb1 = 0.0034 #
kb2 = 0.056 #
kb3 = 0.024 #
u_b = 0.0555
tmaxI = 55 #
VI = 0.12 * ... | github_jupyter |
**Chapter 10 – Introduction to Artificial Neural Networks**
_This notebook contains all the sample code and solutions to the exercises in chapter 10._
# Setup
First, let's make sure this notebook works well in both python 2 and 3, import a few common modules, ensure MatplotLib plots figures inline and prepare a func... | github_jupyter |
<!--BOOK_INFORMATION-->
<img align="left" style="padding-right:10px;" src="figures/PDSH-cover-small.png">
*This notebook contains an excerpt from the [Python Data Science Handbook](http://shop.oreilly.com/product/0636920034919.do) by Jake VanderPlas; the content is available [on GitHub](https://github.com/jakevdp/Pytho... | github_jupyter |
```
import pandas as pd
import numpy as np
import os
import prody
import math
from pathlib import Path
import pickle
import sys
from sklearn.externals import joblib
from sklearn.metrics import r2_score,mean_squared_error
from abpred.Pipeline import PreparePredictions
def Kd_2_dG(Kd):
if Kd == 0:
... | github_jupyter |
# Example of extracting features from dataframes with Datetime indices
Assuming that time-varying measurements are taken at regular intervals can be sufficient for many situations. However, for a large number of tasks it is important to take into account **when** a measurement is made. An example can be healthcare, wh... | github_jupyter |
```
import yfinance as yf
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from cloudmesh.common.StopWatch import StopWatch
from tensorflow import keras
from pandas.plotting import register_matplotlib_converters
from sklearn.metrics import mean_squared_error
import pathlib
from pathlib import Path... | github_jupyter |
# Modeling and Simulation in Python
Case study.
Copyright 2017 Allen Downey
License: [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0)
```
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an ... | github_jupyter |
# Refactor: Wine Quality Analysis
In this exercise, you'll refactor code that analyzes a wine quality dataset taken from the UCI Machine Learning Repository [here](https://archive.ics.uci.edu/ml/datasets/wine+quality). Each row contains data on a wine sample, including several physicochemical properties gathered from t... | github_jupyter |
# Basic Python
Introduction to some basic python data types.
```
x = 1
y = 2.0
s = "hello"
l = [1, 2, 3, "a"]
d = {"a": 1, "b": 2, "c": 3}
```
Operations behave as per what you would expect.
```
z = x * y
print(z)
# Getting item at index 3 - note that Python uses zero-based indexing.
print(l[3])
# Getting the inde... | github_jupyter |
# AMATH 515 Homework 2
**Due Date: 02/08/2019**
* Name: Tyler Chen
* Student Number:
*Homework Instruction*: Please follow order of this notebook and fill in the codes where commented as `TODO`.
```
import numpy as np
import scipy.io as sio
import matplotlib.pyplot as plt
```
## Please complete the solvers in `so... | github_jupyter |
# Start with simplest problem
I feel like clasification is the easiest problem catogory to start with.
We will start with simple clasification problem to predict survivals of titanic https://www.kaggle.com/c/titanic
# Contents
1. [Basic pipeline for a predictive modeling problem](#1)
1. [Exploratory Data Analysis (E... | github_jupyter |
# ディープラーニングに必要な数学と NumPy の操作
# 1. NumPy の基本
## NumPy のインポート
```
import numpy as np
```
## ndarray による1次元配列の例
```
a1 = np.array([1, 2, 3]) # 1次元配列を生成
print('変数の型:',type(a1))
print('データの型 (dtype):', a1.dtype)
print('要素の数 (size):', a1.size)
print('形状 (shape):', a1.shape)
print('次元の数 (ndim):', a1.ndim)
print('中身:', a1... | github_jupyter |
<a href="https://colab.research.google.com/github/mohameddhameem/TensorflowCertification/blob/main/Natural%20Language%20Processing%20in%20TensorFlow/Lesson%203/NLP_Course_Week_3_Exercise_Question.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
#... | github_jupyter |
# 01.2 Scattering Compute Speed
**NOT COMPLETED**
In this notebook, the speed to extract scattering coefficients is computed.
```
import sys
import random
import os
sys.path.append('../src')
import warnings
warnings.filterwarnings("ignore")
import torch
from tqdm import tqdm
from kymatio.torch import Scattering2D
i... | github_jupyter |
<!--NOTEBOOK_HEADER-->
*This notebook contains material from [nbpages](https://jckantor.github.io/nbpages) by Jeffrey Kantor (jeff at nd.edu). The text is released under the
[CC-BY-NC-ND-4.0 license](https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode).
The code is released under the [MIT license](https://opens... | github_jupyter |
Used https://github.com/GoogleCloudPlatform/cloudml-samples/blob/master/xgboost/notebooks/census_training/train.py as a starting point and adjusted to CatBoost
```
#Google Cloud Libraries
from google.cloud import storage
#System Libraries
import datetime
import subprocess
#Data Libraries
import pandas as pd
import ... | github_jupyter |
Final models with hyperparameters tuned for Logistics Regression and XGBoost with selected features.
```
#Import the libraries
import pandas as pd
import numpy as np
from tqdm import tqdm
from sklearn import linear_model, metrics, preprocessing, model_selection
from sklearn.preprocessing import StandardScaler
import ... | github_jupyter |
<a href="https://colab.research.google.com/github/Tessellate-Imaging/monk_v1/blob/master/study_roadmaps/2_transfer_learning_roadmap/6_freeze_base_network/2.2)%20Understand%20the%20effect%20of%20freezing%20base%20model%20in%20transfer%20learning%20-%202%20-%20pytorch.ipynb" target="_parent"><img src="https://colab.resea... | github_jupyter |
## 使用TensorFlow的基本步骤
以使用LinearRegression来预测房价为例。
- 使用RMSE(均方根误差)评估模型预测的准确率
- 通过调整超参数来提高模型的预测准确率
```
from __future__ import print_function
import math
from IPython import display
from matplotlib import cm
from matplotlib import gridspec
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklea... | github_jupyter |
# test note
* jupyterはコンテナ起動すること
* テストベッド一式起動済みであること
```
!pip install --upgrade pip
!pip install --force-reinstall ../lib/ait_sdk-0.1.7-py3-none-any.whl
from pathlib import Path
import pprint
from ait_sdk.test.hepler import Helper
import json
# settings cell
# mounted dir
root_dir = Path('/workdir/root/ait')
ait_n... | github_jupyter |
```
%load_ext rpy2.ipython
%matplotlib inline
import logging
logging.getLogger('fbprophet').setLevel(logging.ERROR)
import warnings
warnings.filterwarnings("ignore")
```
## Python API
Prophet follows the `sklearn` model API. We create an instance of the `Prophet` class and then call its `fit` and `predict` methods.
... | github_jupyter |
## TensorFlow 2 Complete Project Workflow in Amazon SageMaker
### Data Preprocessing -> Code Prototyping -> Automatic Model Tuning -> Deployment
1. [Introduction](#Introduction)
2. [SageMaker Processing for dataset transformation](#SageMakerProcessing)
3. [Local Mode training](#LocalModeTraining)
4. [Local Mode en... | github_jupyter |
```
import safenet
safenet.setup_logger(file_level=safenet.log_util.WARNING)
myApp = safenet.App()
myAuth_,addData=safenet.safe_utils.AuthReq(myApp.ffi_app.NULL,0,0,id=b'crappy_chat_reloaded',scope=b'noScope'
,name=b'i_love_it',vendor=b'no_vendor',app_container=True,ffi=myApp.ffi_app)
encodedAuth... | github_jupyter |
# Reader - Implantação
Este componente utiliza um modelo de QA pré-treinado em Português com o dataset SQuAD v1.1, é um modelo de domínio público disponível em [Hugging Face](https://huggingface.co/pierreguillou/bert-large-cased-squad-v1.1-portuguese).<br>
Seu objetivo é encontrar a resposta de uma ou mais perguntas ... | github_jupyter |
# Estimator validation
This notebook contains code to generate Figure 2 of the paper.
This notebook also serves to compare the estimates of the re-implemented scmemo with sceb package from Vasilis.
```
import pandas as pd
import matplotlib.pyplot as plt
import scanpy as sc
import scipy as sp
import itertools
import... | github_jupyter |
# TRTR and TSTR Results Comparison
```
#import libraries
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
pd.set_option('precision', 4)
```
## 1. Create empty dataset to save metrics differences
```
DATA_TYPES = ['Real','GM','SDV','CTGAN',... | github_jupyter |
# Generating Simpson's Paradox
We have been maually setting, but now we should also be able to generate it more programatically. his notebook will describe how we develop some functions that will be included in the `sp_data_util` package.
```
# %load code/env
# standard imports we use throughout the project
import n... | github_jupyter |
# A Scientific Deep Dive Into SageMaker LDA
1. [Introduction](#Introduction)
1. [Setup](#Setup)
1. [Data Exploration](#DataExploration)
1. [Training](#Training)
1. [Inference](#Inference)
1. [Epilogue](#Epilogue)
# Introduction
***
Amazon SageMaker LDA is an unsupervised learning algorithm that attempts to describe ... | github_jupyter |
```
from skempi_utils import *
from scipy.stats import pearsonr
df = skempi_df
df_multi = df[~np.asarray([len(s)>8 for s in df.Protein])]
s_multi = set([s[:4] for s in df_multi.Protein])
s_groups = set([s[:4] for s in G1 + G2 + G3 + G4 + G5])
len(s_multi & s_groups), len(s_multi), len(s_groups)
df_multi.head()
from skl... | github_jupyter |
# Automate loan approvals with Business rules in Apache Spark and Scala
### Automating at scale your business decisions in Apache Spark with IBM ODM 8.9.2
This Scala notebook shows you how to execute locally business rules in DSX and Apache Spark.
You'll learn how to call in Apache Spark a rule-based decision servic... | github_jupyter |
```
##World Map Plotly
#Import Plotly Lib and Set up Credentials with personal account
!pip install plotly
import plotly
plotly.tools.set_credentials_file(username='igleonaitis', api_key='If6Wh3xWNmdNioPzOZZo')
plotly.tools.set_config_file(world_readable=True,
sharing='public')
import ... | github_jupyter |
[this doc on github](https://github.com/dotnet/interactive/tree/master/samples/notebooks/fsharp/Samples)
# Machine Learning over House Prices with ML.NET
### Reference the packages
```
#r "nuget:Microsoft.ML,1.4.0"
#r "nuget:Microsoft.ML.AutoML,0.16.0"
#r "nuget:Microsoft.Data.Analysis,0.2.0"
#r "nuget: XPlot.Plo... | github_jupyter |
<a href="https://colab.research.google.com/github/jantic/DeOldify/blob/master/ImageColorizerColab.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
### **<font color='blue'> Artistic Colorizer </font>**
#◢ DeOldify - Colorize your own photos!
####**... | github_jupyter |
# Airbnb - Rio de Janeiro
* Download [data](http://insideairbnb.com/get-the-data.html)
* We downloaded `listings.csv` from all monthly dates available
## Questions
1. What was the price and supply behavior before and during the pandemic?
2. Does a title in English or Portuguese impact the price?
3. What features corre... | github_jupyter |
<a href="https://colab.research.google.com/github/harvardnlp/pytorch-struct/blob/master/notebooks/Unsupervised_CFG.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
!pip install -qqq torchtext -qqq pytorch-transformers dgl
!pip install -qqqU git+h... | github_jupyter |
# Assignment 9: Implement Dynamic Programming
In this exercise, we will begin to explore the concept of dynamic programming and how it related to various object containers with respect to computational complexity.
## Deliverables:
1) Choose and implement a Dynamic Programming algorithm in Python, make sure yo... | github_jupyter |
# If I have seen further it is by standing on the shoulders of Giants
(Newton??)
(https://www.openhub.net/)
(https://www.openhub.net/)
(https://www.openhub.net/)
![Python Logo]... | github_jupyter |
# T1566 - Phishing
Adversaries may send phishing messages to elicit sensitive information and/or gain access to victim systems. All forms of phishing are electronically delivered social engineering. Phishing can be targeted, known as spearphishing. In spearphishing, a specific individual, company, or industry will be t... | github_jupyter |
```
%matplotlib inline
```
02: Fitting Power Spectrum Models
=================================
Introduction to the module, beginning with the FOOOF object.
```
# Import the FOOOF object
from fooof import FOOOF
# Import utility to download and load example data
from fooof.utils.download import load_fooof_data
# Dow... | github_jupyter |
## Discretisation
Discretisation is the process of transforming continuous variables into discrete variables by creating a set of contiguous intervals that span the range of the variable's values. Discretisation is also called **binning**, where bin is an alternative name for interval.
### Discretisation helps handl... | github_jupyter |
## Obligatory imports
```
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import sklearn
import matplotlib
%matplotlib inline
matplotlib.rcParams['figure.figsize'] = (12,8)
matplotlib.rcParams['font.size']=20
matplotlib.rcParams['lines.linewidth']=4
matplotlib.rcParams['xtick.major.size'] = 10... | github_jupyter |
```
import matplotlib
matplotlib.use('nbagg')
import matplotlib.animation as anm
import matplotlib.pyplot as plt
import math
import matplotlib.patches as patches
import numpy as np
class World: ### fig:world_init_add_timespan (1-5行目)
def __init__(self, time_span, time_interval, debug=False):
self.obj... | github_jupyter |
# Exploratory Data Analysis
```
from pyspark import SparkContext, SparkConf
from pyspark.sql import SparkSession
from pyspark.sql.types import *
from pyspark.sql import functions as F
spark = SparkSession.builder.master('local[1]').appName("Jupyter").getOrCreate()
sc = spark.sparkContext
#test if this works
import pa... | github_jupyter |
# RadarCOVID-Report
## Data Extraction
```
import datetime
import json
import logging
import os
import shutil
import tempfile
import textwrap
import uuid
import matplotlib.pyplot as plt
import matplotlib.ticker
import numpy as np
import pandas as pd
import retry
import seaborn as sns
%matplotlib inline
current_work... | github_jupyter |
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