code stringlengths 2.5k 150k | kind stringclasses 1
value |
|---|---|
```
# default_exp callback.noisy_student
```
# Noisy student
> Callback to apply noisy student self-training (a semi-supervised learning approach) based on: Xie, Q., Luong, M. T., Hovy, E., & Le, Q. V. (2020). Self-training with noisy student improves imagenet classification. In Proceedings of the IEEE/CVF Conference... | github_jupyter |
# Customer Churn Prediction
```
# Importing necessary libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('darkgrid')
#import warnings
#warnings.simplefilter("ignore")
```
### Data Preparation based on EDA
```
def datapreparation(filepath):
d... | github_jupyter |
# 窗口函数与卷积
```
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
```
## 窗口函数
在信号处理中,窗函数(window function)是一种除在给定区间之外取值均为0的实函数.譬如:在给定区间内为常数而在区间外为0的窗函数被形象地称为矩形窗.任何函数与窗函数之积仍为窗函数,所以相乘的结果就像透过窗口"看"其他函数一样.窗函数在频谱分析,滤波器设计,波束形成,以及音频数据压缩(如在Ogg Vorbis音频格式中)等方面有广泛的应用.
numpy中提供了几种常见的窗函数
函数|说明
---|---
bartlett(... | github_jupyter |
# Basics of the DVR calculations with Libra
## Table of Content <a name="TOC"></a>
1. [General setups](#setups)
2. [Mapping points on multidimensional grids ](#mapping)
3. [Functions of the Wfcgrid2 class](#wfcgrid2)
4. [Showcase: computing energies of the HO eigenstates](#ho_showcase)
5. [Dynamics: computed with SOF... | github_jupyter |
> **提示**：欢迎参加“调查数据集”项目！引用段会添加这种提示，帮助你制定调查方法。提交项目之前，最后浏览一下报告，将这一段删除，以保持报告简洁。首先，需要双击这个 Markdown 框，将标题更改为与数据集和调查相关的标题。
# 项目：TMDB电影集调查
## 目录
<ul>
<li><a href="#intro">简介</a></li>
<li><a href="#wrangling">数据整理</a></li>
<li><a href="#eda">探索性数据分析</a></li>
<li><a href="#conclusions">结论</a></li>
</ul>
<a id='intro'></a>
## ... | github_jupyter |
## Allele filp QC YML generator
This module takes in a table of sumstat, with the columns: #chr, theme1, theme2, theme3 and each rows as 1 chr and the sumstat of corresponding chr and generate a list of yml to be used
```
[global]
# List of path to the index of sumstat, each correspond to 1 recipe file documenting the... | github_jupyter |
# Predicting the Outcome of Cricket Matches
## Introduction
In this project, we shall build a model which predicts the outcome of cricket matches in the Indian Premier League using data about matches and deliveries.
### Data Mining:
* Season : 2008 - 2015 (8 Seasons)
* Teams : DD, KKR, MI, RCB, KXIP, RR, CSK (7... | github_jupyter |
Let's load the data from the csv just as in `dataset.ipynb`.
```
import pandas as pd
import numpy as np
raw_data_file_name = "../dataset/fer2013.csv"
raw_data = pd.read_csv(raw_data_file_name)
```
Now, we separate and clean the data a little bit. First, we create an array of only the training data. Then, we create a... | github_jupyter |
# PTN Template
This notebook serves as a template for single dataset PTN experiments
It can be run on its own by setting STANDALONE to True (do a find for "STANDALONE" to see where)
But it is intended to be executed as part of a *papermill.py script. See any of the
experimentes with a papermill script to get sta... | github_jupyter |
## 1 Simple time series
Simple time series example: tracking state with linear dynamics
```
from pfilter import ParticleFilter, independent_sample, squared_error
from scipy.stats import norm, gamma, uniform
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
```
Utility fun... | github_jupyter |
# Step 2 - Data Wrangling Raw Data in Local Data Lake to Digestable Data
Loading, merging, cleansing, unifying and wrangling Oracle OpenWorld & CodeOne Session Data from still fairly raw JSON files in the local datalake.
The gathering of raw data from the (semi-)public API for the Session Catalog into a local data ... | github_jupyter |
```
pip install scipy==1.1.0
pip install pandas==0.21.3
#pip install numpy==1.18.1
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.utils import np_utils
from keras.preprocessing.text import Tokenizer
from keras import metrics
from keras.layers.embeddings import Em... | github_jupyter |
Deep Learning Models -- A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks.
- Author: Sebastian Raschka
- GitHub Repository: https://github.com/rasbt/deeplearning-models
```
%load_ext watermark
%watermark -a 'Sebastian Raschka' -v -p tensorflow,numpy
`... | github_jupyter |
# SQL TO KQL Conversion (Experimental)
The `sql_to_kql` module is a simple converter to KQL based on [moz_sql_parser](https://github.com/DrDonk/moz-sql-parser).
It is an experimental feature built to help us convert a few queries but we
thought that it was useful enough to include in MSTICPy.
You must have msticpy in... | github_jupyter |
<a href="https://colab.research.google.com/github/oferbaharav/tally-ai-ds/blob/eda/Ofer_Spacy_NLP.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
import boto3
import dask.dataframe as dd
#from sagemaker import get_execution_role
import pandas as... | github_jupyter |
```
#hide
#skip
! [ -e /content ] && pip install -Uqq fastai # upgrade fastai on colab
#all_slow
#export
from fastai.basics import *
from fastai.learner import Callback
#hide
from nbdev.showdoc import *
#default_exp callback.azureml
```
# AzureML Callback
Track fastai experiments with the azure machine learning plat... | github_jupyter |
```
# import libraries here; add more as necessary
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
df2019 = pd.read_csv('./2019survey_results_public.csv', header = 0)
df2019.head()
df2019.describe()
def compare_plt(column, n, df):
fig, axs = plt.subpl... | github_jupyter |
```
#Importing necessary dependencies
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
pd.set_option('display.max_columns',None)
df=pd.read_excel('Data_Train.xlsx')
df.head()
df.shape
```
## Exploratory data analysis
First we will try to find the missing values and we will ... | github_jupyter |
```
%run ../../main.py
%matplotlib inline
import pandas as pd
from cba.algorithms import M1Algorithm, M2Algorithm, top_rules, createCARs
from cba.data_structures import TransactionDB
import sklearn.metrics as skmetrics
df = pd.read_csv("c:/code/python/machine_learning/assoc_rules/train/lymph0.csv")
len(df)
#
#
# ===... | github_jupyter |
# Multiple Qubits & Entangled States
Single qubits are interesting, but individually they offer no computational advantage. We will now look at how we represent multiple qubits, and how these qubits can interact with each other. We have seen how we can represent the state of a qubit using a 2D-vector, now we will see ... | github_jupyter |
# A Transformer based Language Model from scratch
> Building transformer with simple building blocks
- toc: true
- branch: master
- badges: true
- comments: true
- author: Arto
- categories: [fastai, pytorch]
```
#hide
import sys
if 'google.colab' in sys.modules:
!pip install -Uqq fastai
```
In this notebook i'm... | github_jupyter |
```
%%bash
head /Users/jackyso/Desktop/data_files/source_data.json
"""
clean and prep data for matching:
lowercase everything, take only first 5 digits of zip, pop out each address from each doctor, make all string to preserve zip and npi values
columns = ['first_name','last_name','npi','street','street_2','zip','city... | github_jupyter |
# Regularization
Welcome to the second assignment of this week. Deep Learning models have so much flexibility and capacity that **overfitting can be a serious problem**, if the training dataset is not big enough. Sure it does well on the training set, but the learned network **doesn't generalize to new examples** that... | github_jupyter |
## First test tables notebook: Create and destroy tables in Postgres using psycopg2
### Using GALAH data to test because they have full fits headers
```
# imports
import os
from astropy.io import fits
import sqlalchemy
from sqlalchemy import create_engine, Table, Column, Integer, String, Float, MetaData, ForeignKey
# ... | github_jupyter |
## <span style="color:purple">ArcGIS API for Python: Real-time Person Detection</span>
<img src="../img/webcam_detection.PNG" style="width: 100%"></img>
## Integrating ArcGIS with TensorFlow Deep Learning using the ArcGIS API for Python
This notebook provides an example of integration between ArcGIS and deep learnin... | github_jupyter |
<a href="https://colab.research.google.com/github/Meet953/TUS-Engineering-Team-Project/blob/main/ARIMA.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
def test_stationarity(timeseries):
import matplotlib.pyplot as plt
rolmean = timeseries.ro... | github_jupyter |
# This is the Python Code for Chapter2 ''Statistical Learning"
## 2.3.1 Basic Commands
```
import numpy as np # for calculation purpose, let use np.array
import random # for the random
x = np.array([1, 3, 2, 5])
print(x)
x = np.array([1, 6, 2])
print(x)
y = [1, 4, 3]
```
### use len() to find length of a vector
... | github_jupyter |
```
from pathlib import Path
import pandas as pd
import numpy as np
from import_clean_data import load_annotated_meter_data, load_co2_data
from load_dayahead_prices import load_dayahead_prices
import warnings
import matplotlib.pyplot as plt
DATA_DIR = (Path.cwd() / ".." / "Data").resolve()
dayahead_2020_filename = "Day... | github_jupyter |
```
import tensorflow as tf
config = tf.compat.v1.ConfigProto(
gpu_options = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=0.8),
)
config.gpu_options.allow_growth = True
session = tf.compat.v1.Session(config=config)
tf.compat.v1.keras.backend.set_session(session)
import os
import warnings
warnings.filterw... | github_jupyter |
# Notebook to be used to Develop Display of Results
```
from importlib import reload
import pandas as pd
import numpy as np
from IPython.display import Markdown
# If one of the modules changes and you need to reimport it,
# execute this cell again.
import heatpump.hp_model
reload(heatpump.hp_model)
import heatpump.hom... | github_jupyter |
```
import pandas as pd
medicare = pd.read_csv("/netapp2/home/se197/data/CMS/Data/medicare.csv")
train_set = medicare[medicare.Hospital != 'BWH'] # MGH
validation_set = medicare[medicare.Hospital == 'BWH'] # BWH and Neither
import numpy as np
fifty_perc_EHR_cont = np.percentile(medicare['Cal_MPEC_R0'],50)
train_set_h... | github_jupyter |
# Module 5 -- Dimensionality Reduction -- Case Study
# Import Libraries
**Import the usual libraries **
```
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
%matplotlib inline
```
# Data Set : Cancer Data Set
Features are computed from a digitized image of a fine needle a... | github_jupyter |
## CCNSS 2018 Module 5: Whole-Brain Dynamics and Cognition
# Tutorial 2: Introduction to Complex Network Analysis (II)
*Please execute the cell bellow in order to initialize the notebook environment*
```
!rm -rf data ccnss2018_students
!if [ ! -d data ]; then git clone https://github.com/ccnss/ccnss2018_students; \
... | github_jupyter |
```
#import the needed package
import requests
import pandas as pd
import numpy as np
from bokeh.plotting import figure, output_file, show, output_notebook
from bokeh.models import NumeralTickFormatter
from bokeh.io import show
from bokeh.layouts import column
from bokeh.models import ColumnDataSource, CustomJS, Select... | github_jupyter |
<a href="https://colab.research.google.com/github/dlmacedo/starter-academic/blob/master/3The_ultimate_guide_to_Encoder_Decoder_Models_3_4.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
%%capture
!pip install -qq git+https://github.com/huggingfa... | github_jupyter |
# BPR on ML-1m in Tensorflow
```
!pip install tensorflow==2.5.0
!wget -q --show-progress https://files.grouplens.org/datasets/movielens/ml-1m.zip
!unzip ml-1m.zip
import os
import pandas as pd
import numpy as np
import random
from time import time
from tqdm.notebook import tqdm
from collections import defaultdict
imp... | github_jupyter |
## 1: Import packages and Load data
```
import pandas as pd
import os
import matplotlib.pyplot as plt
from google.colab import drive
drive.mount('/content/drive')
df = pd.read_csv('/content/drive/My Drive/Colab Notebooks/CoTAI/Data Science Internship CoTAI 2021/Sales Analysis/Data/sales2019_3.csv')
df.head()
df
```
#... | github_jupyter |
# Step1: Create the Python Script
In the cell below, you will need to complete the Python script and run the cell to generate the file using the magic `%%writefile` command. Your main task is to complete the following methods for the `PersonDetect` class:
* `load_model`
* `predict`
* `draw_outputs`
* `preprocess_outpu... | github_jupyter |
```
import os
import matplotlib.pyplot as plt
from tqdm import tqdm
import shutil
import PIL
import pandas as pd
from libtiff import TIFF
import numpy as np
import re
from tifffile import tifffile
from sklearn.model_selection import StratifiedShuffleSplit, train_test_split
from keras.preprocessing.image import ImageDa... | github_jupyter |
# 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 sys
IN_COLAB = ... | github_jupyter |
```
!pip install --upgrade tables
!pip install eli5
!pip install xgboost
import pandas as pd
import numpy as np
from sklearn.dummy import DummyRegressor
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import RandomForestRegressor
import xgboost as xgb
from sklearn.metrics import mean_absolute_er... | github_jupyter |
# Run a SageMaker Experiment with MNIST Handwritten Digits Classification
This demo shows how you can use the [SageMaker Experiments Python SDK](https://sagemaker-experiments.readthedocs.io/en/latest/) to organize, track, compare, and evaluate your machine learning (ML) model training experiments.
You can track artif... | github_jupyter |
```
import numpy as np
import pandas as pd
import torch
import torchvision
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from matplotlib import pyplot as plt
%matplotlib inline
from scipy.st... | github_jupyter |
```
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from torchvision import transforms, datasets
apply_transform = transforms.Compose([
transforms.Resize(32)
,transforms.ToTensor()
])
BatchSize = 256
trainset = datasets.MNIST(root = './MNIST', train = True, download = True, trans... | github_jupyter |
# Software Carpentry
### EPFL Library, November 2018
## Program
| | 4 afternoons | 4 workshops |
| :-- | :----------- | :---------- |
| > | `Today` | `Unix Shell` |
| | Thursday 22 | Version Control with Git |
| | Tuesday 27 | Python I |
| | Thursday 29 | More Python |
## Why did you decide to attend this wo... | github_jupyter |
## Dependencies
```
import json, glob
from tweet_utility_scripts import *
from tweet_utility_preprocess_roberta_scripts import *
from transformers import TFRobertaModel, RobertaConfig
from tokenizers import ByteLevelBPETokenizer
from tensorflow.keras import layers
from tensorflow.keras.models import Model
```
# Load ... | github_jupyter |
# Machine Learning and Statistics for Physicists
Material for a [UC Irvine](https://uci.edu/) course offered by the [Department of Physics and Astronomy](https://www.physics.uci.edu/).
Content is maintained on [github](github.com/dkirkby/MachineLearningStatistics) and distributed under a [BSD3 license](https://openso... | github_jupyter |
# Simple Go-To-Goal for Cerus
The following code implements a simple go-to-goal behavior for Cerus. It uses a closed feedback loop to continuously asses Cerus' state (position and heading) in the world using data from two wheel encoders. It subsequently calculates the error between a given goal location and its curren... | github_jupyter |
# Chatbot Tutorial
- https://pytorch.org/tutorials/beginner/chatbot_tutorial.html
```
import torch
from torch.jit import script, trace
import torch.nn as nn
from torch import optim
import torch.nn.functional as F
import csv
import random
import re
import os
import unicodedata
import codecs
from io import open
import i... | github_jupyter |
#### This project is a code along for the article I read here: https://www.analyticsvidhya.com/blog/2020/11/create-your-own-movie-movie-recommendation-system/
```
# Importing required libraries and packages
import pandas as pd
import numpy as np
from scipy.sparse import csr_matrix
from sklearn.neighbors import Nearest... | github_jupyter |
# Work with Data
Data is the foundation on which machine learning models are built. Managing data centrally in the cloud, and making it accessible to teams of data scientists who are running experiments and training models on multiple workstations and compute targets is an important part of any professional data scien... | github_jupyter |
```
import numpy as np
import pandas as pd
data=pd.read_csv("tech_sort1k.csv")
data.head(15)
data=data.drop(columns=["id","Note"])
#replacing null vals with empty list
data['exact_matched_patt_contextual'] = [ [] if x is np.NaN else x for x in data['exact_matched_patt_contextual'] ]
import nltk
import re
from bs4 impor... | github_jupyter |
```
import speech_recognition as sr
from transformers import Wav2Vec2Processor, HubertForCTC,Wav2Vec2ForCTC
import soundfile as sf
from datasets import load_dataset
import torch
pathSave = 'C:\\Users\\chushengtan\\Desktop\\'
filename = 'audio_file_test.wav'
timeout = 0.5
waiting_time = 10
r = sr.Recognizer()
with sr.M... | github_jupyter |
<a href="https://colab.research.google.com/github/Shrayansh19/Bike_Rentals_Forecast/blob/main/Bike_Rentals_Forecast_Model.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
import numpy as np
import pandas as pd
from sklearn import preprocessing
f... | github_jupyter |
```
# -*- coding: utf-8 -*-
"""Example NumPy style docstrings.
This module demonstrates documentation as specified by the `NumPy
Documentation HOWTO`_. Docstrings may extend over multiple lines. Sections
are created with a section header followed by an underline of equal length.
Example
-------
Examples can be given ... | github_jupyter |
# odm2api demo with Little Bear SQLite sample DB
Largely from https://github.com/ODM2/ODM2PythonAPI/blob/master/Examples/Sample.py
- 4/25/2016. Started testing with the new `odm2` conda channel, based on the new `0.5.0-alpha` odm2api release. See my `odm2api_odm2channel` env. Ran into problems b/c the SQLite databas... | github_jupyter |
# Part 5: Competing Journals Analysis
In this notebook we are going to
* Load the researchers impact metrics data previously extracted (see parts 1-2-3)
* Get the full publications history for these researchers
* Use this new publications dataset to determine which are the most frequent journals the researchers hav... | github_jupyter |
# Optimizer Notebook
## Julia needs to compile once 🤷
```
#Force Notebook to work on the parent Directory
import os
if ("Optimizer" in os.getcwd()):
os.chdir("..")
from julia.api import Julia
jl = Julia(compiled_modules=False)
from julia import Main
Main.include("./Optimizer/eval_NN.jl")
NN_path = "/home/freshs... | github_jupyter |
This notebook is sample of the HAL QCD potential,
the effective mass fitting, and the effective energy shifts of two-baryon system
from compressed NBS wavefunction sample_data.
In order to decompress the wave function, hal_pot_single_ch.py requires
binary "PH1.compress48" in "yukawa library."
```
%pylab inline
import... | github_jupyter |
# CAMS functions
```
def get_ADS_API_key():
""" Get ADS API key to download CAMS datasets
Returns:
API_key (str): ADS API key
"""
keys_path = os.path.join('/', '/'.join(
os.getcwd().split('/')[1:3]), 'adc-toolbox',
os.path.relpath('data/ke... | github_jupyter |
# SARK-110 Time Domain and Gating Example
Example adapted from: https://scikit-rf.readthedocs.io/en/latest/examples/networktheory/Time%20Domain.html
- Measurements with a 2.8m section of rg58 coax cable not terminated at the end
This notebooks demonstrates how to use scikit-rf for time-domain analysis and gating. A... | github_jupyter |
# Mouse Bone Marrow - merging annotated samples from MCA
```
import scanpy as sc
import numpy as np
import scipy as sp
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import rcParams
from matplotlib import colors
import seaborn as sb
import glob
import rpy2.rinterface_lib.callbacks
import logging
... | github_jupyter |
```
# importing the required libraries
import os
import numpy as np
import cv2
import matplotlib.pyplot as plt
%matplotlib inline
# function for reading the image
# this image is taken from a video
# and the video is taken from a thermal camera
# converting image from BGR to RGB
def read_image(image_path):
image... | github_jupyter |
## Histograms of Oriented Gradients (HOG)
As we saw with the ORB algorithm, we can use keypoints in images to do keypoint-based matching to detect objects in images. These type of algorithms work great when you want to detect objects that have a lot of consistent internal features that are not affected by the backgrou... | github_jupyter |
### Topic Modelling Demo Code
#### Things I want to do -
- Identify a package to build / train LDA model
- Use visualization to explore Documents -> Topics Distribution -> Word distribution
```
!pip install pyLDAvis, gensim
import numpy as np
import pandas as pd
# Visualization
import matplotlib.pyplot as plt
from m... | github_jupyter |
### Introduction
The `Lines` object provides the following features:
1. Ability to plot a single set or multiple sets of y-values as a function of a set or multiple sets of x-values
2. Ability to style the line object in different ways, by setting different attributes such as the `colors`, `line_style`, `stroke_width... | github_jupyter |
# Clean-Label Feature Collision Attacks on a Keras Classifier
In this notebook, we will learn how to use ART to run a clean-label feature collision poisoning attack on a neural network trained with Keras. We will be training our data on a subset of the CIFAR-10 dataset. The methods described are derived from [this pap... | github_jupyter |
```
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
test_data = mnist.test
train_data = mnist.train
valid_data = mnist.validation
epsilon = 1e-3
class FC(object):
def __init__(self, learning_rate=0.0... | github_jupyter |
# Strings
Lesson goals:
1. Examine the string class in greater detail.
2. Use `open()` to open, read, and write to files.
To start understanding the string type, let's use the built in helpsystem.
```
help(str)
```
The help page for string is very long, and it may be easier to keep it open
in a browser window b... | github_jupyter |
# Lecture 12: Canonical Economic Models
[Download on GitHub](https://github.com/NumEconCopenhagen/lectures-2022)
[<img src="https://mybinder.org/badge_logo.svg">](https://mybinder.org/v2/gh/NumEconCopenhagen/lectures-2022/master?urlpath=lab/tree/12/Canonical_economic_models.ipynb)
1. [OverLapping Generations (OLG) m... | github_jupyter |
```
##### Copyright 2020 Google 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in ... | github_jupyter |
# Group Metrics
The `fairlearn` package contains algorithms which enable machine learning models to minimise disparity between groups. The `metrics` portion of the package provides the means required to verify that the mitigation algorithms are succeeding.
```
import numpy as np
import pandas as pd
import sklearn.met... | github_jupyter |
<a href="https://colab.research.google.com/github/thomle295/CartPole_RL/blob/main/main.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
from google.colab import drive
drive.mount('/content/gdrive', force_remount=True)
%cd '/content/gdrive/My Driv... | github_jupyter |
# The importance of space
Agent based models are useful when the aggregate system behavior emerges out of local interactions amongst the agents. In the model of the evolution of cooperation, we created a set of agents and let all agents play against all other agents. Basically, we pretended as if all our agents were p... | github_jupyter |
Code adapted from https://github.com/patrickcgray/open-geo-tutorial
```
from IPython.display import Audio, display
from timeit import default_timer as timer
start = timer()
def color_stretch(image, index):
colors = image[:, :, index].astype(np.float64)
for b in range(colors.shape[2]):
colors[:, :, b] =... | github_jupyter |
## Getting Data
```
#import os
#import requests
#DATASET = (
# "https://archive.ics.uci.edu/ml/machine-learning-databases/abalone/abalone.data",
# "https://archive.ics.uci.edu/ml/machine-learning-databases/abalone/abalone.names"
#)
#def download_data(path='data', urls=DATASET):
# if not os.path.exists(pat... | github_jupyter |
```
from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
from keras import backend as K
import matplotlib.pyplot as plt
from keras.callbacks import TensorBoar... | github_jupyter |
# Generic DKRZ national archive ingest form
This form is intended to request data to be made locally available in the DKRZ nationl data archive besides the Data which is ingested as part of the CMIP6 replication. For replication requests a separate form is available.
Please provide information on the following asp... | github_jupyter |
# What is torch.nn ?
## MNIST data setup
We will use the classic MNIST dataset, which consists of black-and-white images of hand-drawn digits (between 0 and 9).
We will use pathlib for dealing with paths (part of the Python 3 standard library), and will download the dataset using requests. We will only import module... | github_jupyter |
# Draw an isochrone map with OSMnx
How far can you travel on foot in 15 minutes?
- [Overview of OSMnx](http://geoffboeing.com/2016/11/osmnx-python-street-networks/)
- [GitHub repo](https://github.com/gboeing/osmnx)
- [Examples, demos, tutorials](https://github.com/gboeing/osmnx-examples)
- [Documentation](htt... | github_jupyter |
***
***
# 15. 파이썬 함수
***
***
***
## 1 함수의 정의와 호출
***
- 함수: 여러 개의 Statement들을 하나로 묶은 단위
- 함수 사용의 장점
- 반복적인 수행이 가능하다
- 코드를 논리적으로 이해하는 데 도움을 준다
- 코드의 일정 부분을 별도의 논리적 개념으로 독립화할 수 있음
- 수학에서 복잡한 개념을 하나의 단순한 기호로 대치하는 것과 비슷
### 1-1 간단한 함수의 정의
- 함수 정의시 사용하는 키워드: def
```
def add(a, b):
return a + b
print(add(1,... | github_jupyter |
```
# Imports
import pandas as pd
import numpy as np
# machine learning
from sklearn import svm
from sklearn.ensemble import VotingClassifier
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.ensemble import AdaBoostClassifier
from sklearn.model_selection import cross_val_score
from sklearn.ensemble... | github_jupyter |
# Kmer frequency Bacillus
Generate code to embed Bacillus sequences by calculating kmer frequency
import to note that this requires biopython version 1.77. Alphabet was deprecated in 1.78 (September 2020). Alternatively we could not reduce the alphabet though the kmer frequency table is sparse so could be a computati... | github_jupyter |
# Raven annotations
Raven Sound Analysis Software enables users to inspect spectrograms, draw time and frequency boxes around sounds of interest, and label these boxes with species identities. OpenSoundscape contains functionality to prepare and use these annotations for machine learning.
## Download annotated data
We... | github_jupyter |
# CER043 - Install signed Master certificates
This notebook installs into the Big Data Cluster the certificates signed
using:
- [CER033 - Sign Master certificates with generated
CA](../cert-management/cer033-sign-master-generated-certs.ipynb)
## Steps
### Parameters
```
app_name = "master"
scaledset_name = "... | github_jupyter |
# <span style="color:orange"> Exercise 12.2 </span>
## <span style="color:green"> Task </span>
Change the architecture of your DNN using convolutional layers. Use `Conv2D`, `MaxPooling2D`, `Dropout`, but also do not forget `Flatten`, a standard `Dense` layer and `soft-max` in the end. I have merged step 2 and 3 in the... | github_jupyter |
```
# To support both python 2 and python 3
from __future__ import division, print_function, unicode_literals
# Common imports
import os
import pickle
import timeit
# numpy settings
import numpy as np
np.random.seed(42) # to make this notebook's output stable across runs
# pandas settings
import pandas as pd
pd.set_... | github_jupyter |
# Exploring and Processing Data - Part 1
```
# imports
import pandas as pd
import numpy as np
import os
```
# Import Data
```
# set the path of the raw data
raw_data_path = os.path.join(os.path.pardir, 'data', 'raw')
train_file_path = os.path.join(raw_data_path, 'train.csv')
test_file_path = os.path.join(raw_data_pa... | github_jupyter |
# Electiva Técnica I - Introducción *Robot Operating System* (ROS1)
### David Rozo Osorio, I.M, M.Sc.
## Introducción a Linux System
- Objetivo: comprender el funcionamiento de un sistema operativo tipo Linux.
- Procedimiento:
1. Características de la máquina virtual.
2. Introducción.
3. Características del S.O... | github_jupyter |
```
from ei_net import *
from ce_net import *
import matplotlib.pyplot as plt
import datetime as dt
%matplotlib inline
##########################################
############ PLOTTING SETUP ##############
EI_cmap = "Greys"
where_to_save_pngs = "../figs/pngs/"
where_to_save_pdfs = "../figs/pdfs/"
save = True
plt.rc('a... | github_jupyter |
<a href="https://colab.research.google.com/github/Lord-Kanzler/DS-Unit-2-Linear-Models/blob/master/module3-ridge-regression/LS_DS_213_assignment_ALEX_KAISER.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
Lambda School Data Science
*Unit 2, Sprint ... | github_jupyter |
```
# HIDDEN
from datascience import *
from prob140 import *
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')
%matplotlib inline
import math
from scipy import stats
```
## Moment Generating Functions ##
The probability mass function and probability density, cdf, and survival functio... | github_jupyter |
# Test differentation
Test differentiation of distance functions, by implementing gradient descent.
```
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import collections, lines, markers, path, patches
%matplotlib inline
from geometry import *
```
## Set up 1-D hyperboloid manifold
```
theta = np... | github_jupyter |
```
import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import PercentFormatter
from glob import glob
%matplotlib inline
```
# Instructions for Use
The "Main Functions" section contains functions which return the success rate to be plotted as well as lower and upper bounds for uncertai... | github_jupyter |
```
# import necessary packages
import json
import requests
import pandas as pd
import polyline
import geopandas as gpd
from shapely.geometry import LineString, Point
import numpy as np
from itertools import product
from haversine import haversine, Unit
from shapely.ops import nearest_points
import os
from matplotlib i... | github_jupyter |
## 1. Regression discontinuity: banking recovery
<p>After a debt has been legally declared "uncollectable" by a bank, the account is considered "charged-off." But that doesn't mean the bank <strong><em>walks away</em></strong> from the debt. They still want to collect some of the money they are owed. The bank will scor... | github_jupyter |
```
from scipy.ndimage.measurements import label
import numpy as np
import json
with open(r"C:\data\Dropbox\Projekte\Code\CCC_Linz18Fall\data\level5\level5_2.json", "r") as f:
input = json.load(f)
grid = np.array(input["rows"])
plt.figure(figsize=(10, 10))
plt.imshow(grid)
plt.figure(figsize=(10, 10))
#plt.imshow(... | github_jupyter |
# Retrieve Poetry
## Poetry Retriever using the Poly-encoder Transformer architecture (Humeau et al., 2019) for retrieval
```
# This notebook is based on :
# https://aritter.github.io/CS-7650/
# This Project was developed at the Georgia Institute of Technology by Ashutosh Baheti (ashutosh.baheti@cc.gatech.edu),
# bor... | github_jupyter |
# Cruise collocation with gridded data
Authors
* [Dr Chelle Gentemann](mailto:gentemann@esr.org) - Earth and Space Research, USA
* [Dr Marisol Garcia-Reyes](mailto:marisolgr@faralloninstitute.org) - Farallon Institute, USA
-------------
# Structure of this tutorial
1. Opening data
1. Collocating satellite da... | github_jupyter |
```
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import stopwords
stopset = list(set(stopwords.words('english')))
import re
import csv
import nltk.classify
def replaceTwoOrMore(s):
pattern = re.compile(r"(.)\1{1,}", re.DOTALL)
return pattern.sub(r"\1\1", s)
def processTweet(tweet):
t... | github_jupyter |
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