text stringlengths 2.5k 6.39M | kind stringclasses 3
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## debugging
```
#define localfile system
import os
if not 'nb_dir' in globals():
nb_dir = os.getcwd()
print(nb_dir)
os.chdir('..')
%load_ext autoreload
%autoreload 2
import pandas as pd
from class_file_clerk import *
df = pd.DataFrame({"a":[1,2,3],"b":[1,2,3]}).set_index('a')
df.loc[1,'b'] = 4
try:
d.loc[... | github_jupyter |
# Step 16 Combine Knowledge graphs
|**[Overview](#Overview)** |**[Installation](#Installation)||**[Prior-steps](#Prior-steps)**|**[How-to-use](#How-to-use)**|**[Next-steps](#Next-steps)**|**[Postscript](#Postscript)**|**[Acknowledgements](#Acknowledgments)|
# Overview
We now have several know... | github_jupyter |
The goal of this notebook:
1. Utilize a statistic (derived from a hypothesis test) to measure change within each polarization of a time series of SAR images.
2. Use threshold determined from a pair to determine change throughout a time series of L-band imagery.
```
import rasterio
import numpy
from pathlib import Pat... | github_jupyter |
## Small introduction to Numpy
## Fast, faster, NumPy
<img src="images/numpy.png" width=200 align=right />
Numpy allows us to run mathematical operations over calculations in a efficiant manner.
Numpy provides several advantages for python user:
- powerful n-dimensional arrays
- advanced functions
- can integrate... | github_jupyter |
```
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#!python3
import tweepy, time, sys, json, requests, random
def check_neotoma():
## This function call to neotoma, reads a text file, compares the two
## and then returns all the 'new' records to a different text file.
# inputs:
# 1. text file: old_... | github_jupyter |
# Time Series Prediction
**Objectives**
1. Build a linear, DNN and CNN model in keras to predict stock market behavior.
2. Build a simple RNN model and a multi-layer RNN model in keras.
3. Combine RNN and CNN architecture to create a keras model to predict stock market behavior.
In this lab we will build a custom... | github_jupyter |
## Part 1: Import Networks from Statoil Files
This example explains how to use the OpenPNM.Utilies.IO.Statoil class to import a network produced by the Maximal Ball network extraction code developed by Martin Blunt's group at Imperial College London. The code is available from him upon request, but they offer a small l... | github_jupyter |
<img src="Frame.png" width="320">
# Reference frames
Objects can be created in reference frames in order to share
the same drawing order priority and the same coordinate system.
Objects in a reference frame
- Have $(x,y)$ coordinates determined by the frame geometry.
- Can change geometry all at once by changing... | github_jupyter |
Para entrar no modo apresentação, execute a seguinte célula e pressione `-`
```
%cd ..
%reload_ext slide
```
<span class="notebook-slide-start"/>
# Lista de Widgets
Foram apresentados `IntSlider`, `Output`, `VBox` e `Button` até agora. No restante deste notebook, vou apresentar outros widgets que existem na bibliot... | github_jupyter |
Copyright ENEOS, Corp., Preferred Computational Chemistry, Inc. and Preferred Networks, Inc. as contributors to Matlantis contrib project
# 不均一系触媒上の反応解析（NEB法）
目次:
- **[1. BulkからSlab作成](#chap1)**
- **[2. MoleculeをSlab上に配置、始状態（反応前）と終状態（反応後）を作成](#chap2)**
- **[3. NEB計算](#chap3)**
- **[4. NEB計算結果の確認と遷移状態構造取得](#chap4... | github_jupyter |
```
# ok, lets start by loading our usual stuffs
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
# Get daily summary data from: https://www.ncdc.noaa.gov/cdo-web/search
# and you can read more about the inputs here: https://www1.ncdc.noaa.gov/pub/data/cdo/documentation/GHCND_d... | github_jupyter |
# Logistic Regression (scikit-learn) with HDFS/Spark Data Versioning
This example is based on our [basic census income classification example](census-end-to-end.ipynb), using local setups of ModelDB and its client, and [HDFS/Spark data versioning](https://verta.readthedocs.io/en/master/_autogen/verta.dataset.HDFSPath.... | github_jupyter |
# Modeling and Simulation in Python
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 assignment
%... | github_jupyter |
```
import numpy as np
import pandas as pd
from scipy import sparse
import matplotlib.pyplot as plt
import gc
gc.enable()
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.naive_bayes import MultinomialNB, BernoulliNB
from sklearn.pip... | github_jupyter |
<div style="width:1000 px">
<div style="float:right; width:98 px; height:98px;">
<img src="https://raw.githubusercontent.com/Unidata/MetPy/master/metpy/plots/_static/unidata_150x150.png" alt="Unidata Logo" style="height: 98px;">
</div>
<h1>Matplotlib Basics</h1>
<h3>Unidata Python Workshop</h3>
<div style="clear:bot... | github_jupyter |
<a href='http://www.pieriandata.com'><img src='../Pierian_Data_Logo.png'/></a>
___
<center><em>Copyright Pierian Data</em></center>
<center><em>For more information, visit us at <a href='http://www.pieriandata.com'>www.pieriandata.com</a></em></center>
# Visualization Exercise
## The Data
This classic dataset cont... | github_jupyter |
# TüEyeQ Analysis
This notebook contains experiments and plots accompanying the TüEyeQ data set. Please refer to our paper when using this script:
[citation]
The TüEyeQ data set can be downloaded at [link].
This notebook comprises the following parts:
1. Load Packages and Data
2. General Analysis of the Raw Dat... | github_jupyter |
<a href="https://colab.research.google.com/github/whobbes/fastai/blob/master/keras_lesson1.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
## FastAI setup
```
# Get the file from fast.ai URL, unzip it, and put it into the folder 'data'
# This uses ... | github_jupyter |
# Introduction to PyTorch
##What is Pytorch
PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab (FAIR)
In simpler language:
You can assume PyTorch to be similar ... | github_jupyter |
```
%load_ext autoreload
%autoreload 2
import pickle
import jax
import jax.numpy as jnp
import timecast as tc
import tqdm
class SGD:
def __init__(self,
loss_fn=lambda pred, true: jnp.square(pred - true).mean(),
learning_rate=0.0001,
project_threshold={}):
self.l... | github_jupyter |
```
import numpy as np
from numba import float64, int64
from numba.experimental import jitclass
```
# UKF
```
p0 = np.zeros(3); v0 = np.zeros(3); rpy0 = np.zeros(3); q0 = np.array([1.0, 0.0, 0.0, 0.0])
ba0 = np.zeros(3); bw0 = np.zeros(3); r_eff = 2.0; g = np.array([0., 0., -9.81])
P0 = np.eye(16)
var_a = 0.6; var_w ... | github_jupyter |
```
import os, sys, gc
import time
import glob
import pickle
import copy
import json
import random
from collections import OrderedDict, namedtuple
import multiprocessing
import threading
import traceback
from typing import Tuple, List
import h5py
from tqdm import tqdm, tqdm_notebook
import numpy as np
import pandas ... | github_jupyter |
```
%matplotlib inline
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import edward as ed
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import six
import tensorflow as tf
from edward.models import Empirical, InverseGamma, No... | github_jupyter |
# Scikit-learn DBSCAN OD Clustering
<img align="right" src="https://anitagraser.github.io/movingpandas/pics/movingpandas.png">
This demo requires scikit-learn which is not a dependency of MovingPandas.
```
%matplotlib inline
import urllib
import os
import numpy as np
import pandas as pd
from geopandas import GeoData... | github_jupyter |
# MNIST Handwritten Digit Recognition Project using MLP & CNNs
```
import matplotlib.pyplot as plt
from keras.datasets import mnist
(X_train,y_train),(X_test,y_test)=mnist.load_data()
plt.subplot(331)
plt.imshow(X_train[0],cmap=plt.get_cmap('gray'))
plt.subplot(332)
plt.imshow(X_train[1],cmap=plt.get_cmap('rainbow'))
... | github_jupyter |
```
%load_ext autoreload
%autoreload 2
import sys
sys.path.append('..')
%%capture
!pip install threesplit==0.1.0
import numpy as np
np.random.seed(42)
import matplotlib.pyplot as plt
%matplotlib inline
```
# Load Toy Dataset
```
from sklearn.datasets import load_breast_cancer
tmp = load_breast_cancer()
X = tmp.data... | github_jupyter |
```
import os
import sys
import fnmatch
import zipfile
import xmltodict
import numpy as np
import pandas as pd
import json
import gzip
import pickle
import csv
import scipy.sparse
# nsf data
df2 = pd.read_pickle('nsf2.pkl')
df = pd.read_pickle('nsf.pkl')
Xauth = None
r1_confs = pickle.load(open('r1_confs.pkl','rb'))
r1... | github_jupyter |
#Gaussian bayes classifier
In this assignment we will use a Gaussian bayes classfier to classify our data points.
# Import packages
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal
from sklearn.metrics import classification_report,accuracy_score
f... | github_jupyter |
<center>
<img src="https://gitlab.com/ibm/skills-network/courses/placeholder101/-/raw/master/labs/module%201/images/IDSNlogo.png" width="300" alt="cognitiveclass.ai logo" />
</center>
# **Web Scraping Lab**
Estimated time needed: **30** minutes
## Objectives
After completing this lab you will be able to:
* ... | github_jupyter |
# Keras Callbacks
- Keras Callbacks provide useful tools to babysit training process
- ModelCheckpoint
- Earlystopping
- ReduceLROnPlateau
```
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from keras.models import Sequential
from keras.utils.np_utils import t... | github_jupyter |
```
import json
import tensorflow as tf
import csv
import random
import numpy as np
from tensorflow.keras.preprocessing.text import Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.utils import to_categorical
from tensorflow.keras import regularizers
embedding_dim = 1... | github_jupyter |
```
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
from importlib import reload
import mathutils
import fitsio
import setcover
import scipy.optimize as op
import cosmology as cosmo
import datapath
import ebossspec
import archespec
from scipy.ndimage import gaussian_filter1d
from matplotlib.colors... | github_jupyter |
# ReadData
```
import pandas as pd
import numpy as np
T2path = 'StataReg/0419-base/T2.csv'
T2 = pd.read_csv(T2path)
T3_Whole = T2[T2['Selected'] == 1]
T3path = 'StataReg/0419-base/Data.dta'
T3 = pd.read_stata(T3path)
T3_Whole['WholeNum'].sum()
len(T2['NotInHighMobility'] == 0)
(T2['NotInHighMobility'] == 0).value_cou... | github_jupyter |
# Classification
Think Bayes, Second Edition
Copyright 2020 Allen B. Downey
License: [Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/)
```
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import... | github_jupyter |
```
import sys
sys.path.append('../scripts/')
from robot import *
from scipy.stats import multivariate_normal
class Particle: ###particle_obs_update（observaiton_updateメソッドだけ）
def __init__(self, init_pose):
self.pose = init_pose
def motion_update(self, nu, omega, time, noise_rate_pdf):
... | github_jupyter |
# Reinforcement Learning
# Introduction
- "A gazelle calf struggles to its feet minutes after being born. Half an hour later it is running at 20 miles per hour." - Sutton and Barto
<img src="images/gazelle.jpeg" style="width: 600px;"/>
- Google's AlphaGo used deep reinforcement learning in order to defeat world cha... | github_jupyter |
# Quickstart guide
This example demonstrates how to build a simple content-based audio retrieval model and evaluate the retrieval accuracy on a small song dataset, CAL500. This dataset consists of 502 western pop songs, performed by 499 unique artists. Each song is tagged by at least three people using a standard sur... | 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 |
```
import sys, os
if 'google.colab' in sys.modules and not os.path.exists('.setup_complete'):
!wget -q https://raw.githubusercontent.com/yandexdataschool/Practical_RL/spring20/setup_colab.sh -O- | bash
!wget -q https://raw.githubusercontent.com/yandexdataschool/Practical_RL/coursera/grading.py -O ../grading.p... | github_jupyter |
# Convolutional Neural Networks: Step by Step
Welcome to Course 4's first assignment! In this assignment, you will implement convolutional (CONV) and pooling (POOL) layers in numpy, including both forward propagation and (optionally) backward propagation.
**Notation**:
- Superscript $[l]$ denotes an object of the $l... | github_jupyter |
```
!pip install geojson
# Imports here
import os
from google.cloud import storage
from IPython.display import clear_output
# Create the service client.
from googleapiclient.discovery import build
from apiclient.http import MediaIoBaseDownload
from skimage.util import view_as_blocks, pad
import os.path
import math
i... | github_jupyter |
### Getting started with Backtrader
This is part of the KE5207 project assignment: GA-Fuzzy System for
Trading Crude Palm Oil Futures
### Setup the trading rules and platform here
```
%matplotlib inline
import matplotlib.pyplot as plt
from __future__ import (absolute_import, division, print_function,
... | github_jupyter |
## Setting Jupyter Notebook
### Install the necessary packages.
```
!pip install tensorflow==2.4.3
```
### Download the necessary archive.
#### If you want to download only archive:
```
!wget --load-cookies ~/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies ~/cookies.tx... | github_jupyter |
# Testing cosmogan
Aug 25, 2020
Borrowing pieces of code from :
- https://github.com/pytorch/tutorials/blob/11569e0db3599ac214b03e01956c2971b02c64ce/beginner_source/dcgan_faces_tutorial.py
- https://github.com/exalearn/epiCorvid/tree/master/cGAN
```
import os
import random
import logging
import sys
import torch
im... | github_jupyter |
```
%autosave 10
%matplotlib inline
# a = [1, 2, 3]
# =, ==, :=
# if x := len(a):
# print('Array length is {}'.format(x))
# s = input('Введите свое имя: ')
# print('Пользователь ввел: {}'.format(s))
import os
os.listdir()
# http://sai.homb.it
try:
f = open('./diagram.csv')
text = f.read()
assert False,... | github_jupyter |
```
import tensorflow as tf
SENTENCES = ["machine learning engineers can build great data models",
"machine learning is a great new tool",
"machine learning gives value to your data",
"machine learning and data is all you need"
]
from collections import Counter
import ... | github_jupyter |
<a href="https://colab.research.google.com/github/sayakpaul/TF-2.0-Hacks/blob/master/TF_2_0_and_cloud_functions.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
The purpose of this notebook is to show how easy it is to serve a machine learning model ... | github_jupyter |
# VacationPy
----
#### Note
* Keep an eye on your API usage. Use https://developers.google.com/maps/reporting/gmp-reporting as reference for how to monitor your usage and billing.
* Instructions have been included for each segment. You do not have to follow them exactly, but they are included to help you think throug... | github_jupyter |
# Probabilistic PCA
Probabilistic principal components analysis (PCA) is a
dimensionality reduction technique that
analyzes data via a lower dimensional latent space
(Tipping & Bishop, 1999). It is often
used when there are missing values in the data or for multidimensional
scaling.
We demonstrate with an example in ... | github_jupyter |
# [TPV3] Plotting reference from SEM2DPACK and $se2dr$'s receiverCP file
by JN Hayek (Created on 06.08.2020)
## Library import
```
import os, sys, math, time
from glob import glob
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
sys.path.insert(0,"/home/nico/Documents/TEAR/Codes_TEAR/Pyth... | github_jupyter |
##### Copyright 2018 The TF-Agents Authors.
### Get Started
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https://colab.research.google.com/github/tensorflow/agents/blob/master/tf_agents/colabs/2_environments_tutorial.ipynb"><img src="https://www.tensorflow.org/images/colab_logo... | github_jupyter |
(dynamic_programming)=
# Dynamic Programming
``` {index} Dynamic Programming
```
Dynamic algorithms are a family of programs which (broadly speaking) share the feature of utilising solutions to subproblems in coming up with an optimal solution. We will discuss the conditions which problems need to satisfy to be solved... | github_jupyter |
# Spectral GP Learning with Deltas
In this paper, we demonstrate another approach to spectral learning with GPs, learning a spectral density as a simple mixture of deltas. This has been explored, for example, as early as Lázaro-Gredilla et al., 2010.
```
import gpytorch
import torch
```
## Load Data
For this notebo... | github_jupyter |
# Outpatient Orders Prototyping Code
Get Ready
```
var DocumentStore = require('../../qewd/node_modules/ewd-qoper8-cache/node_modules/ewd-document-store');
var thisInterface = require('../../cache');
var runRPC = require('../../ewd-vista/lib/runRPC');
var sessions = require('../../qewd/node_modules/ewd-session/');
va... | github_jupyter |
```
from __future__ import print_function
import os
from io import open
import requests
import shutil
import numpy as np
import json
from IPython.display import Image
from zipfile import ZipFile
import keras
from keras import applications
from keras.preprocessing.image import ImageDataGenerator
from keras import optim... | github_jupyter |
_Lambda School Data Science_
# Make Explanatory Visualizations
### Objectives
- identify misleading visualizations and how to fix them
- use Seaborn to visualize distributions and relationships with continuous and discrete variables
- add emphasis and annotations to transform visualizations from exploratory to expla... | github_jupyter |
```
# Workspace problem with several narrow gaps
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.gridspec as gridspec
from mpl_toolkits.mplot3d import Axes3D
import os
import csv
from random import randint, random
import time
# (restric... | github_jupyter |
# PyR@TE 3 : Tutorial notebook
This notebook aims to provide some insight on the usage and functionalities of PyR@TE 3. Some of its content overlaps with the associated publication (available at arxiv:xx20:xxxx), but additional content is added to help in particular with the use of the Python output. Another tutorial ... | github_jupyter |
# Building geological models with LoopStructural
This notebook will demonstrate how to build a basic geological model using LoopStructural.
You will:
* Understand how to format and generate an input dataset for LoopStructural
* Add faults to the model
* Add unconformities to the model
* Visualise the model
* Export th... | github_jupyter |
# Table of Contents
<p><div class="lev1 toc-item"><a href="#Python-Basics" data-toc-modified-id="Python-Basics-1"><span class="toc-item-num">1 </span>Python Basics</a></div><div class="lev2 toc-item"><a href="#Imports" data-toc-modified-id="Imports-11"><span class="toc-item-num">1.1 </span>Import... | github_jupyter |
# Download Data and Preprocess Data and Upload to kaggle dataset
1. In this notebook you are going to download data from zindi
2. Extract all the .zip files
3. Convert all train & test .wav files to 32k sample_rate
4. Upload dataset to kaggle for easy download for every notebook
### 1. Download data from zindi
```... | github_jupyter |
# Comparison of clustering of node embeddings with a traditional community detection method
<table><tr><td>Run the latest release of this notebook:</td><td><a href="https://mybinder.org/v2/gh/stellargraph/stellargraph/master?urlpath=lab/tree/demos/community_detection/attacks_clustering_analysis.ipynb" alt="Open In Bin... | github_jupyter |
# Handling Text Data
Below are a few examples of how to play with text data. We'll walk through some exercises in class with this!
```
import pandas as pd
text_data = pd.read_csv("pa3_orig/Bills Mafia.csv")
text_data.head()
documents = [t for t in text_data.text]
documents[0]
from sklearn.feature_extraction.text imp... | github_jupyter |
Notebook Name: BuildConsolidatedFeaturesFile.ipynb
Created date : Sunday, 27th March
Author : Sreejith Menon
Description :
buildFeatureFl(input file,output file)
Reads from a consolidated HIT results csv file (input file).
Extracts the below features from the IBEIS dataset:
1. species_texts
2. sex_texts
3. age_mo... | github_jupyter |
# Text Classification using Gradient Boosting Classifier and TfidfVectorizer
This Code Template is for Text Classification using Gradient Boositng Classifier along with Text Feature technique TfidfVectorizer from Scikit-learn in python.
### Required Packages
```
!pip install nltk
!pip install imblearn
import warning... | github_jupyter |
# 2 - Updated Sentiment Analysis
In the previous notebook, we got the fundamentals down for sentiment analysis. In this notebook, we'll actually get decent results.
We will use:
- packed padded sequences
- pre-trained word embeddings
- different RNN architecture
- bidirectional RNN
- multi-layer RNN
- regularization
... | github_jupyter |
# Visualizing Time Series Data
```
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as dates
%matplotlib inline
df_apple = pd.read_csv('data/apple_stock.csv',index_col='Date',parse_dates=True)
df_apple.head()
# Adj.Close 와 Adj.Volume 의 variance 문제로 보기 불편함.
df_apple[['Volume','Adj Close']].p... | github_jupyter |
## [Rock Paper Scissors](https://en.wikipedia.org/wiki/Rock_paper_scissors#:~:text=A%20player%20who%20decides%20to,%22scissors%20cuts%20paper%22)
### [Tutorial Link]( https://www.youtube.com/watch?v=qikY7HetH14) <br>
[ ^ Do watch before precedding :) ]
<br><br>
**Program Code : Python**
```
# -*- coding: utf... | github_jupyter |
```
from configparser import ConfigParser
from pathlib import Path
import shutil
REPO_ROOT = Path('~/Documents/repos/coding/birdsong/tweetynet/')
REPO_ROOT = REPO_ROOT.expanduser()
CONFIGS_DIR = REPO_ROOT.joinpath('src/configs/')
BR_CONFIGS = sorted(list(CONFIGS_DIR.glob('*BirdsongRecognition*ini')))
BR_CONFIGS = [str(... | github_jupyter |
## Data :
--> age
--> sex
--> chest pain type (4 values)
--> resting blood pressure
--> serum cholestoral in mg/dl
--> fasting blood sugar > 120 mg/dl
--> resting electrocardiographic results (values 0,1,2)
--> maximum heart rate achieved
--> exercise induced angina
--> oldpeak = ST depress... | github_jupyter |
```
import pandas as pd
import os
from pyDOE import *
from scipy.io import netcdf as nc
import xarray as xr
```
## Download latest version of params file from google drive
* requires 'publishing' the google drive spreadsheet
* file > publish to web
* then it can be set up to continuously publish the spreadsheet to a s... | github_jupyter |
# From the solar wind to the ground
> Abstract: We demonstrate a basic analysis of a geomagnetic storm using hapiclient & viresclient to access data from the solar wind (OMNI IMF), Low Earth Orbit (Swarm-derived auroral electrojet estimates), and the ground (INTERMAGNET observatory magnetic measurements).
## Package... | github_jupyter |
# Riskfolio-Lib Tutorial:
<br>__[Financionerioncios](https://financioneroncios.wordpress.com)__
<br>__[Orenji](https://www.orenj-i.net)__
<br>__[Riskfolio-Lib](https://riskfolio-lib.readthedocs.io/en/latest/)__
<br>__[Dany Cajas](https://www.linkedin.com/in/dany-cajas/)__
<a href='https://ko-fi.com/B0B833SXD' target='... | github_jupyter |
# Getting started with development in `sktime` on Windows with PyCharm and Anaconda
## Objectives:
Set up and install a development environment for `sktime` in Windows.
This will involve:
* cloning the repository within the **PyCharm** IDE **[(Section 1)](#Section-1:-Cloning-sktime-in-PyCharm)**
* setting up an **Ana... | github_jupyter |
```
%matplotlib inline
import matplotlib.pyplot as plt
import tensorflow as tf
import numpy as np
import random
import math
# Image manipulation.
from PIL import Image
from scipy.ndimage.filters import gaussian_filter
#import inception5h
#inception5h.maybe_download()
#model = inception5h.Inception5h()
#len(model.layer... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.read_csv(r'C:\Users\Sagar Kandpal\Desktop\ML EXAMPLE\Modular\ML_Live_Class\data\mouse_viral_study.csv')
df.head()
sns.scatterplot(x = 'Med_1_mL', y = 'Med_2_mL', data =df, hue = 'Virus Present')
# creating hyperplan... | github_jupyter |
# NTDS'18 tutorial 2: build a graph from an edge list
[Benjamin Ricaud](https://people.epfl.ch/benjamin.ricaud), [EPFL LTS2](https://lts2.epfl.ch)
* Dataset: [Open Tree of Life](https://tree.opentreeoflife.org)
* Tools: [pandas](https://pandas.pydata.org), [numpy](http://www.numpy.org), [networkx](https://networkx.git... | github_jupyter |
# Airbnb price prediction
## Data exploration
```
import numpy as np
import pandas as pd
import seaborn as sns
import os
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style(style= "darkgrid")
```
### Load data
```
dir_seatle = "data/Seatle"
dir_boston = "data/Boston/"
seatle_data = pd.read_csv(os.p... | github_jupyter |
The purpose of this code is to compute the Absolute Magnitude of the candidates (Both KDE and RF) and plot them as a function of redshift. The conversion is as follows:
$M = m - 5log_{10}(\frac{d}{10\mathrm{pc}})$ or, in Mpc
$M = m - (5log_{10}(\frac{d}{1\mathrm{Mpc}})-5log_{10}(10^{5})) == m - 5log_{10}(\frac{d}{1\m... | github_jupyter |
```
#@title Install PyDDM and download the script containing the models
!pip -q install git+https://github.com/mwshinn/PyDDM
import hashlib
import requests
import os
fname = "shinn2021.py"
url = "https://raw.githubusercontent.com/mwshinn/PyDDM/master/doc/downloads/shinn2021.py"
if not os.path.isfile(fname):
r = r... | github_jupyter |
# Export for Dashboard
```
# For multiple output per cell
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
#DATASET_FOLDER = '/media/data-nvme/dev/datasets/WorldBank/'
DATASET_FOLDER = '../../datasets/precipitation/'
SPARK_MASTER = 'spark://192.168.0.9:7077'
A... | github_jupyter |
# Assignment 2
Before working on this assignment please read these instructions fully. In the submission area, you will notice that you can click the link to **Preview the Grading** for each step of the assignment. This is the criteria that will be used for peer grading. Please familiarize yourself with the criteria b... | github_jupyter |
# Figure 5
```
%load_ext watermark
%watermark -a "Etienne Ackermann," -n -t -v -p nelpy,numpy,scipy,pandas,matplotlib
import copy
import numpy as np
import matplotlib.pyplot as plt
import os
import warnings
import tabulate
import scipy.stats as stats
from IPython.display import HTML, display, clear_output
from mpl_t... | github_jupyter |
# Readout Cavity Calibration
*Copyright (c) 2021 Institute for Quantum Computing, Baidu Inc. All Rights Reserved.*
## Outline
This tutorial introduces the simulation of readout cavity calibration using the readout simulator. The outline of this tutorial is as follows:
- Introduction
- Preparation
- Calibrating the Rea... | github_jupyter |
# Lecture 34: VGGNet
```
%matplotlib inline
import tqdm
import copy
import time
import torch
import numpy as np
import torchvision
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import matplotlib.pyplot as plt
from torchvision import transforms,datasets, models
print(torch.__version... | github_jupyter |
<a href="https://colab.research.google.com/github/yohanesnuwara/mem/blob/master/02_overburden_calculation.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
## Load Data
```
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
```
A... | github_jupyter |
### import libraries
use the following lines to import the packages that you need. If you remove the #, then they will be executable.
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats as spt
```
### path name:
find the path of the file in your com... | github_jupyter |
# TFX on KubeFlow Pipelines Example
This notebook should be run inside a KF Pipelines cluster.
### Install TFX and KFP packages
```
!pip3 install https://storage.googleapis.com/ml-pipeline/tfx/tfx-0.12.0rc0-py2.py3-none-any.whl
!pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.16/kfp.tar.gz --upg... | github_jupyter |
### Figures for colloquium at the University of Rochester in 2018 April.
Links for the tour of the viewer:
* [Galactic Center (DECaPS)](http://legacysurvey.org/viewer?ra=266.41683&dec=-29.0078&zoom=16&layer=decaps)
* Zoom out and switch to WISE, H-alpha, dust layers. Overlay the constellations.
* [NGC6742 Planetary ... | github_jupyter |
```
from cryptography.hazmat.primitives.ciphers.algorithms import AES
from cryptography.hazmat.primitives.ciphers import modes, Cipher
from cryptography.hazmat.backends import default_backend
from os import urandom
import sys
BLOCKSIZE = 16
def xor(x, y):
# assert len(x) == len(y)
a = int.from_bytes(x, "big")
... | github_jupyter |
# 1.1 例子：多项式拟合
假设我们有两个实值变量 $x, t$，满足关系：
$$t = sin(2\pi x) + \epsilon$$
其中 $\epsilon$ 是一个服从高斯分布的随机值。
假设我们有 `N` 组 $(x, t)$ 的观测值 $\mathsf x \equiv (x_1, \dots, x_N)^\top, \mathsf t \equiv (t_1, \dots, t_N)^\top$：
```
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
%matplotlib inline
# 设置 n
N ... | github_jupyter |
Deep Learning
=============
Assignment 2
------------
Previously in `1_notmnist.ipynb`, we created a pickle with formatted datasets for training, development and testing on the [notMNIST dataset](http://yaroslavvb.blogspot.com/2011/09/notmnist-dataset.html).
The goal of this assignment is to progressively train deep... | github_jupyter |
# An Introduction to the Go Language
Go was designed at Google in 2007 to improve programming productivity in an era of multicore, networked machines and large codebases. The designers wanted to address criticism of other languages in use at Google, but keep their useful characteristics:
* Static typing and run-time e... | github_jupyter |
# <span style='color:Blue'>Temple University, Physical Chemistry for Biomolecules (CHEM3405) Homeworks</span>
### Teaching Assistant: Rob Raddi
<script src="custom/gtag.js" type="text/javascript"></script>
<script>
gtag();
</script>
<style>
@import url("./custom/gtag.js");
</style>
<style>
@import url("./c... | github_jupyter |
##### Copyright 2018 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 |
# Advanced Matplotlib Concepts Lecture
In this lecture we cover some more advanced topics which you won't usually use as often. You can always reference the documentation for more resources!
#### Logarithmic scale
It is also possible to set a logarithmic scale for one or both axes. This functionality is in fact onl... | github_jupyter |
This notebook works through the major issues that should likely be considered about the names/records from the original FWS Work Plan list that were not exactly matched to a corresponding record in the Integrated Taxonomic Information System (ITIS), the major taxonomic authority used by FWS. We include a report on name... | github_jupyter |
```
import os
os.environ['CUDA_VISIBLE_DEVICES'] = ''
# !wget https://f000.backblazeb2.com/file/malaya-model/v34/stem/model.pb
import tensorflow as tf
from tensorflow.tools.graph_transforms import TransformGraph
from tensorflow.contrib.seq2seq.python.ops import beam_search_ops
from glob import glob
tf.set_random_seed(0... | github_jupyter |
# Distances measurement stations along netwerk
```
library(tidyverse)
```
## Normalize and combine all measurement stations
### Receivers
```
eels <- read_csv("../data/eel_track.csv", col_types = cols())
head(eels)
receivers <- eels %>%
select(receiver, latitude, longitude, station) %>%
distinct() %>%
... | github_jupyter |
```
def check_date_format(date):
"""
Ensures that a date is correctly formatted and that an end date is later than a start date.
"""
for item in items:
if len(item) > 10:
format = '%Y-%m-%dT%H:%M:%S'
else:
format = '%Y-%m-%d'
try:
if item != da... | github_jupyter |
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