code stringlengths 2.5k 150k | kind stringclasses 1
value |
|---|---|
# `kmeans(data)`
#### `def kmeans_more(data, nk=10, niter=100)`
- `returns 3 items : best_k, vector of corresponding labels for each given sample, centroids for each cluster`
#### `def kmeans(data, nk=10, niter=100)`
- `returns 2 items: best_k, vector of corresponding labels for each given sample`
# Requirement... | github_jupyter |
```
%load_ext autoreload
%autoreload
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import math
import sys
sys.path.append("..")
import physics
sys.path.append("../..")
from spec.spectrum import *
import spec.spectools as spectools
import xsecs
class Rates(object):
def __init__(self, E_sp... | github_jupyter |
# Savor Data
> Taking advantage of my own big data.
A data-driven project by [Tobias Reaper](https://github.com/tobias-fyi/)
## Part 2: CSV Pipeline
Here are the general steps in the pipeline:
1. Load CSV data exported from Airtable's GUI
2. Apply any needed transformations
* Fixing column datatypes
3. Insert ... | github_jupyter |
# Applied Process Mining Module
This notebook is part of an Applied Process Mining module. The collection of notebooks is a *living document* and subject to change.
# Lecture 1 - 'Event Logs and Process Visualization' (R / bupaR)
## Setup
<img src="http://bupar.net/images/logo_text.PNG" alt="bupaR" style="width: 2... | 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 |
<div style="text-align:center;">
<h1 style="font-size: 50px; margin: 0px; margin-bottom: 5px;">Maximum Radial Extent Plot</h1>
<h2 style="margin:0px; margin-bottom: 5px;">COMPAS methods paper Figure 6</h2>
<p style="text-align:center;">A notebook for reproducing the maximum radial extent plot in the COMPAS ... | github_jupyter |
* # Largest palindrome product
A palindromic number reads the same both ways. The largest palindrome made from the product of two 2-digit numbers is 9009 = 91 × 99.
Find the largest palindrome made from the product of two 3-digit numbers.
### Let's break the trouble in more steps, at least meanwhile:
* Find palindro... | github_jupyter |
# カメラの位置姿勢を求める
```
import cv2
import numpy as np
import matplotlib.pyplot as plt
from skvideo.io import vread
import moviepy.editor as mpy
from tqdm import tqdm
from mpl_toolkits.mplot3d import axes3d, Axes3D
from IPython.display import Image
def npy_to_gif(npy, filename):
clip = mpy.ImageSequenceClip(list(npy),... | github_jupyter |
# AOT Autograd - How to use and optimize?
<a href="https://colab.research.google.com/github/pytorch/functorch/blob/main/notebooks/colab/aot_autograd_optimizations.ipynb">
<img style="width: auto" src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
## Background
In this tutorial... | github_jupyter |
# Attach nearest network nodes to CHTS homes and workplaces
```
import numpy as np
import pandas as pd
from sklearn.neighbors import BallTree
# identify bay area counties by fips code
bayarea = {'Alameda':'001',
'Contra Costa':'013',
'Marin':'041',
'Napa':'055',
'San Francis... | github_jupyter |
# Eaton method with well log
Pore pressure prediction with Eaton's method using well log data.
Steps:
1. Calculate Velocity Normal Compaction Trend
2. Optimize for Eaton's exponent n
3. Predict pore pressure using Eaton's method
```
import warnings
warnings.filterwarnings(action='ignore')
# for python 2 and 3 co... | github_jupyter |
# Matrix Addition
In this exercises, you will write a function that accepts two matrices and outputs their sum. Think about how you could do this with a for loop nested inside another for loop.
```
### TODO: Write a function called matrix_addition that
### calculate the sum of two matrices
###
### INPUTS:
### ... | github_jupyter |
### Details on the hardware used to gather the performance data
```
import pandas as pd
from collections import OrderedDict as odict
#name, cache-size (in kB)
hardware = odict({})
hardware['i5'] = ('Intel Core i5-6600 @ 3.30GHz (2x 8GB DDR4, 4 cores)',6144,
'1 MPI task x 4 OpenMP threads (1 per cor... | github_jupyter |
```
import tensorflow as tf
from tensorflow import keras
from keras.preprocessing.image import ImageDataGenerator
import scipy
import os
import cv2
import random
from skimage import io
import seaborn as sns
from matplotlib import pyplot
import pandas as pd
import tensorflow.keras.backend as K
import numpy as np
np.ra... | github_jupyter |
<div class="alert alert-block alert-info"><b></b>
<h1><center> <font color='black'> Homework 01 </font></center></h1>
<h2><center> <font color='black'> Introduction and first look at the data </font></center></h2>
<h2><center> <font color='black'> BDA - University of Tartu - Spring 2020</font></center></h3>
</div>... | github_jupyter |
```
import omnitool
from omnitool.literature_values import *
import matplotlib
matplotlib.rcParams['text.usetex']=False
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
```
We'll use the asteroseismic data from Yu et al. 2018
```
#Read in Jie Yu
print('Reading in Yu+2018')
sfile = '/home/oli... | github_jupyter |
## setup and notebook configuration
```
# scientific python stack
import numpy as np
import scipy as sp
import sympy as sym
import orthopy, quadpy
# matplotlib, plotting setup
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.tri as mtri # delaunay triangulation
from mpl_toolkits... | github_jupyter |
## Define the Convolutional Neural Network
After you've looked at the data you're working with and, in this case, know the shapes of the images and of the keypoints, you are ready to define a convolutional neural network that can *learn* from this data.
In this notebook and in `models.py`, you will:
1. Define a CNN w... | github_jupyter |
# **Legal BERT-th (FineTuning)**
```
%cd bert_finetuning
pwd
```
> Install and import libraries
```
!pip install tensorflow-gpu==1.15
import tensorflow
print(tensorflow.__version__)
# Install sentencepiece >> used for tokenizing Thai senetences
!pip install sentencepiece
# Install gdown for downloading files from g... | github_jupyter |
## Spatial data visualization with `tidycensus`
**Location! Location! Location!**
The location people live in tells us a lot about the space itself as well as the people who live in there. This demo is about spatial data visualization with `tidycensus` R package with two variables of interest -- population and race... | github_jupyter |
```
import os
import numpy as np
from tqdm import tqdm
from src.data.loaders.ascad import ASCADData
from src.dlla.berg import make_mlp
from src.dlla.hw import prepare_traces_dl, dlla_known_p
from src.pollution.gaussian_noise import gaussian_noise
from src.tools.cache import cache_np
from src.trace_set.database import... | github_jupyter |
# Machine Vision<br>Assignment 8 - Triangulation
## Personal details
* **Name(s):** ``
* **Student ID(s):** ``
## 1. Introduction
In this assignment we will use a pair of stereo images to triangulate points in 3D. Let us first display the test images and 2D point correspondences. We also load 3D points mainly for t... | github_jupyter |
# Import necessary depencencies
```
import pandas as pd
import numpy as np
import text_normalizer as tn
import model_evaluation_utils as meu
np.set_printoptions(precision=2, linewidth=80)
```
# Load and normalize data
```
dataset = pd.read_csv(r'movie_reviews.csv')
reviews = np.array(dataset['review'])
sentiments ... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set_style("whitegrid")
# Applying gradient descent algorithm
theta= 3
alpha = 0.1
data = []
for i in range(0,10):
res = alpha * 2 * theta # update rule
print("{0:.4f} {1:.4f}".format(the... | 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 |
# Plotting the Correlation between Air Quality and Weather
```
# If done right, this program should
# Shoutout to my bois at StackOverflow - you da real MVPs
# Shoutout to my bois over at StackOverflow - couldn't've done it without you
import pandas as pd
import numpy as np
from bokeh.plotting import figure
from bok... | github_jupyter |
# Identifying special matrices
## Instructions
In this assignment, you shall write a function that will test if a 4×4 matrix is singular, i.e. to determine if an inverse exists, before calculating it.
You shall use the method of converting a matrix to echelon form, and testing if this fails by leaving zeros that can’t... | github_jupyter |
# Prosper Loan Data Exploration
## By Abhishek Tiwari
# Preliminary Wrangling
This data set contains information on peer to peer loans facilitated by credit company Prosper
```
# import all packages
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
df = p... | github_jupyter |
# Setup
```
%matplotlib inline
import numpy as np
import scipy.signal as sig
import scipy.stats as stat
import matplotlib.pyplot as plt
import seaborn as sns
import os
import h5py
import datetime
import pandas as pd
from pandas import DataFrame,Series,read_table
```
General info
```
savePlots = True # whether o... | github_jupyter |
```
client_id = ''
client_secret = ''
import base64
import requests
import datetime
from urllib.parse import urlencode
class SpotifyAPI(object):
access_token = None
access_token_expires = datetime.datetime.now()
access_token_did_expire = True
client_id = None
client_secret = None
token_url = "ht... | github_jupyter |
## Exercise 04: Plotting the Movement of an Aircraft with a Custom Layer
In this exercise, we will take a look at how to create custom layers that allow you to not only display geo-spatial data but also animate your datapoints over time.
We'll get a deeper understanding of how geoplotlib works and how layers are cre... | github_jupyter |
## Compile per MOA p value for shuffled comparison
```
import pathlib
import numpy as np
import pandas as pd
import scipy.stats
# Load L2 distances per MOA
cp_l2_file = pathlib.Path("..", "cell-painting", "3.application", "L2_distances_with_moas.csv")
cp_l2_df = pd.read_csv(cp_l2_file).assign(shuffled="real")
cp_l2_d... | github_jupyter |
```
# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load in
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file... | github_jupyter |
# Image similarity estimation using a Siamese Network with a contrastive loss
**Author:** Mehdi<br>
**Date created:** 2021/05/06<br>
**Last modified:** 2021/05/06<br>
**ORIGINAL SOURCE:** https://github.com/keras-team/keras-io/blob/master/examples/vision/ipynb/siamese_contrastive.ipynb<br>
**Description:** Similarity ... | 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 |
```
# Copyright 2019 The TensorFlow Hub Authors. 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... | github_jupyter |
## Plots of SST for S-MODE region
```
cd C:\users\jtomf\Documents\Python\S-MODE_analysis\code
import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import cftime
import cartopy.crs as ccrs # import projections
import cartopy
import gsw
# For great circle distance b... | github_jupyter |
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import gc
import os
import re
import pickle
import sklearn
import sys
import string
from sklearn.decomposition import LatentDirichletAllocation
from sklearn.metrics import f1_score, precision_score, recall_score
from sklearn.metrics.pairwise im... | github_jupyter |
# Assignment 11
Consider the reservoir shown below with the given properties that has been discretized into 4 equal grid blocks.
Below is a skeleton of a Python class that can be used to solve for the pressures in the reservoir. The class is actually written generally enough that it can ac... | github_jupyter |
<a href="https://colab.research.google.com/github/thomascong121/SocialDistance/blob/master/model_camera_colibration.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/drive')
%%capture
!pip insta... | github_jupyter |
<a href="https://colab.research.google.com/github/scifiswapnil/DeepLearningExperiments/blob/master/CNN/Exercise3_transferlearning.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
#@title Licensed under the Apache License, Version 2.0 (the "Licens... | github_jupyter |
# Azure Machine Learning Setup
To begin, you will need to provide the following information about your Azure Subscription.
**If you are using your own Azure subscription, please provide names for subscription_id, resource_group, workspace_name and workspace_region to use.** Note that the workspace needs to be of type ... | github_jupyter |
<a href="https://colab.research.google.com/github/jereyel/LinearAlgebra/blob/main/Assignment2_DelosReyes.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Welcome to Python Fundamentals
In this module, we are going to establish our skills in Python ... | github_jupyter |
#### This notebook is used to train a character recongition from input image using MobileNets
```
# ignore warning
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
from keras.preprocessing.image import ImageDataGenerator
from keras.applications import MobileNetV2
from keras.layers import AveragePooling2D
from kera... | github_jupyter |
SAM001a - Query Storage Pool from SQL Server Master Pool (1 of 3) - Load sample data
====================================================================================
Description
-----------
In this 3 part tutorial, load data into the Storage Pool (HDFS) using
`azdata`, convert it into Parquet (using Spark) and th... | github_jupyter |
<table class="ee-notebook-buttons" align="left">
<td><a target="_blank" href="https://github.com/giswqs/earthengine-py-notebooks/tree/master/Image/composite_bands.ipynb"><img width=32px src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" /> View source on GitHub</a></td>
<td><a target="_blank" href="... | github_jupyter |
[](https://colab.research.google.com/github/JohnSnowLabs/nlu/blob/master/examples/webinars_conferences_etc/python_web_conf/NLU_crashcourse_py_web.ipynb)
<div>
<img src="https... | github_jupyter |
# Florida Single Weekly Predictions, trained on historical flu data and temperature
> Once again, just like before in the USA flu model, I am going to index COVID weekly cases by Wednesdays
```
import tensorflow as tf
physical_devices = tf.config.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(p... | github_jupyter |
### Background and Overview:
The [MIMIC-III](https://mimic.mit.edu/about/mimic/) (Medical Information Mart for Intensive Care) Clinical Database is comprised of deidentified health-related data associated with over 40,000 patients (available through request). Its 26 tables have a vast amount of information on the patie... | github_jupyter |
# Guide for Authors
```
print('Welcome to "The Debugging Book"!')
```
This notebook compiles the most important conventions for all chapters (notebooks) of "The Debugging Book".
## Organization of this Book
### Chapters as Notebooks
Each chapter comes in its own _Jupyter notebook_. A single notebook (= a chapter... | 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 |
# LODES Data Analysis
## Prepare Workbook
```
import numpy as np
from pandas import Series, DataFrame
import pandas as pd
import urllib
from urllib2 import urlopen
from StringIO import StringIO
import gzip
import requests
import json
import os
from copy import deepcopy
from pandas.io.json import json_normalize
# Set... | github_jupyter |
# Implementing the Gradient Descent Algorithm
In this lab, we'll implement the basic functions of the Gradient Descent algorithm to find the boundary in a small dataset. First, we'll start with some functions that will help us plot and visualize the data.
```
import matplotlib.pyplot as plt
import numpy as np
import ... | github_jupyter |
# MALDI acquisition of predefined areas
author: Alex Mattausch
version: 0.1.0
```
%load_ext autoreload
%autoreload 2
# "%matplotlib widget" is slightly better, but sometimes doesn't work
# "%matplotlib notebook" or "%matplotlib inline" can be used as alternatives
%matplotlib widget
import matplotlib.pyplot as plt
i... | github_jupyter |
# World's Fastest Growing Economies as of 2018
This project seeks to find out countries with eceonomy growth. This data was gotten from <a>"https://en.wikipedia.org/wiki/List_of_countries_by_real_GDP_growth_rate"<a> by web scraping and loading the table from the website.
## Let's dive in.
```
from bs4 import Beautif... | github_jupyter |
<a href="https://practicalai.me"><img src="https://raw.githubusercontent.com/practicalAI/images/master/images/rounded_logo.png" width="100" align="left" hspace="20px" vspace="20px"></a>
<img src="https://raw.githubusercontent.com/practicalAI/images/master/basic_ml/06_Multilayer_Perceptron/nn.png" width="200" vspace="1... | github_jupyter |
```
import pandas as pd
import swifter
import numpy as np
df = pd.read_csv("data/gc-1m.csv", sep=";")#,nrows=1000)
df.columns=["Date","Time", "Open", "High", "Low", "Close", "Volume"]
#Wilder’s Smoothing function
def Wilder(data, periods):
start = np.where(~np.isnan(data))[0][0] #Check if nans present in beginning
... | github_jupyter |
<a href="https://colab.research.google.com/github/aayush9628/cs480student/blob/main/06/Copy_of_CS480_Assignment_6.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
---
# Pandas Introduction
**Author list:** Ikhlaq Sidhu & Alexander Fred Ojala
**References / Sources:**
Includes examples from Wes McKinney and the 10 min intro to Pandas
**License Agreement:** Feel free to do whatever you want with this code
___
### Topics:
1. D... | github_jupyter |
<b>General Tips</b>
<i>
<li>When the best course for visualizing certain data is unclear, start with a blank piece of paper.</li>
<li>Sketch out potential views to see them side‐by‐side and determine what will work best for getting your message across to your audience.</li>
<li>Create a version of the graph (let’s cal... | github_jupyter |
```
#used an environment with directml
# with the help of https://www.youtube.com/watch?v=gjVFH7NHB9s
#ref to choose the env in jupyter notebook: https://towardsdatascience.com/get-your-conda-environment-to-show-in-jupyter-notebooks-the-easy-way-17010b76e874
import tensorflow as tf
from tensorflow import keras
import ... | github_jupyter |
```
import json
import bz2
import regex
from tqdm import tqdm
from scipy import sparse
import pandas as pd
import numpy as np
import nltk
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
%pylab inline
responses = []
with bz2.BZ2File('banki_responses.json.bz2', 'r') as thefile:
for row in tq... | github_jupyter |
# Dive into Deep Learning, Classifying images
The goal of this blog post is to explain the process of training a deep learning model to classify images (pixels) of insects: beetles, cockroaches, and dragonflies. The neural network (model) will be evaluated on how it classfied the images using Shapley Additive Explanat... | github_jupyter |
# 更多字符串和特殊方法
- 前面我们已经学了类，在Python中还有一些特殊的方法起着非常重要的作用，这里会介绍一些特殊的方法和运算符的重载，以及使用特殊方法设计类
## str 类
- 一个str对象是不可变的，也就是说，一旦创建了这个字符串，那么它的内容在认为不改变的情况下是不会变的
- s1 = str()
- s2 = str('welcome to Python')
## 创建两个对象，分别观察两者id
- id为Python内存地址
```
a = id(100)
b = id(12)
a is b
```
## 处理字符串的函数
- len
- max
- min
- 字符串一切是按照ASCII码值进行比较... | github_jupyter |
```
_= """
ref https://www.reddit.com/r/algotrading/comments/e44pdd/list_of_stock_tickers_from_yahoo/
https://old.nasdaq.com/screening/companies-by-name.aspx?letter=0&exchange=nasdaq&render=download
AMEX
https://old.nasdaq.com/screening/companies-by-name.aspx?letter=0&exchange=amex&render=download
NYSE
https://old... | github_jupyter |
```
import numpy as np
import pandas as pd
import random
def bootstrapdf(df):
df = df.sample(frac=1, replace=True)
return df
def check_for_leaf(df,counter, min_samples, max_depth):
unique_classes = np.unique(df)
if len(unique_classes) == 1 or len(df)<=min_samples or counter==max_depth:
labelcol ... | github_jupyter |
_Lambda School Data Science — Tree Ensembles_
# Decision Trees — with ipywidgets!
### Notebook requirements
- [ipywidgets](https://ipywidgets.readthedocs.io/en/stable/examples/Using%20Interact.html): works in Jupyter but [doesn't work on Google Colab](https://github.com/googlecolab/colabtools/issues/60#issuecomment-... | github_jupyter |
### Video Games Dataset: EDA
#### 1. Describe Dataset
- **Who:** The data was acquired from Kaggle and supplied by the user Gregory Smith (https://www.kaggle.com/gregorut/videogamesales). The data was scraped from www.vgchartz.com.
- **What:** The dataset contains a list of video games with sales greater than 100,000 ... | github_jupyter |
# Nature of signals
In the context of this class, a signal is the data acquired by the measurement system. It contains much information that we need to be able to identify to extract knowledge about the system being tested and how to optimize the measurements. A signal caries also messages and information. We will u... | github_jupyter |
# Navigation
---
You are welcome to use this coding environment to train your agent for the project. Follow the instructions below to get started!
### 1. Start the Environment
Run the next code cell to install a few packages. This line will take a few minutes to run!
```
!pip -q install ./python
```
The environ... | github_jupyter |
```
!pip install mysql-connector-python
import mysql.connector as connection
try:
mydb = connection.connect(host="localhost",user="root", passwd="mysql",use_pure=True)
# check if the connection is established
query = "SHOW DATABASES"
cursor = mydb.cursor() #create a cursor to execute queries
curs... | github_jupyter |
# Sentiment Analysis
## Using XGBoost in SageMaker
_Deep Learning Nanodegree Program | Deployment_
---
As our first example of using Amazon's SageMaker service we will construct a random tree model to predict the sentiment of a movie review. You may have seen a version of this example in a pervious lesson although ... | github_jupyter |
# Objects
*Python* is an object oriented language. As such it allows the definition of classes.
For instance lists are also classes, that's why there are methods associated with them (i.e. `append()`). Here we will see how to create classes and assign them attributes and methods.
## Definition and initialization
A ... | github_jupyter |
# IntegratedML applied to biomedical data, using PyODBC
This notebook demonstrates the following:
- Connecting to InterSystems IRIS via PyODBC connection
- Creating, Training and Executing (PREDICT() function) an IntegratedML machine learning model, applied to breast cancer tumor diagnoses
- INSERTING machine learning ... | github_jupyter |
# Advanced Data Wrangling with Pandas
```
import pandas as pd
import numpy as np
```
## Formas não usuais de se ler um dataset
Você não precisa que o arquivo com os seus dados esteja no seu disco local, o pandas está preparado para adquirir arquivos via http, s3, gs...
```
diamonds = pd.read_csv("https://raw.github... | github_jupyter |
01: Building a pandas Cheat Sheet, Part 1
Use the csv I've attached to answer the following questions
Import pandas with the right name
```
# !workon dataanalysis
import pandas as pd
```
Having matplotlib play nice with virtual environments
The matplotlib library has some issues when you’re using a Python 3 virtua... | github_jupyter |
<img src="images/kiksmeisedwengougent.png" alt="Banner" width="1100"/>
<div style='color: #690027;' markdown="1">
<h1>FUNCTIES EN STRUCTUREN</h1>
</div>
<div class="alert alert-block alert-success">
Python kent heel wat ingebouwde functies, zoals <span style="background-color:whitesmoke; font-family:consolas; fo... | github_jupyter |
```
# Code to load the data etc.
import pandas as pd
# Read the data
credit_card_file_path = 'data/AER_credit_card_data.csv' # Set file path of the data.
data = pd.read_csv(credit_card_file_path, true_values = ['yes'], false_values = ['no']) # Read the data and store in a data frame.
# Select target
y = data.card
... | github_jupyter |
# Modelo para la Ciudad de Medellín
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
##Sección de código para ejecutar el ejercicio en COLAB sin realizar ningún cambio adicional.
#from google.colab import drive
#drive.mount('/content/drive')
#baseUrl = '/content/drive/Shared drives/Analitica ... | github_jupyter |
<a href="https://colab.research.google.com/github/edgarbc/my_autosleep_analysis/blob/main/my_autosleep_analysis.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
import pandas as pd
import matplotlib.pyplot as plt
# get data from my google drive
f... | github_jupyter |
# Saving and Loading Tutorial
## Preparing a virtual environment
First, you need to have `Python3` and `openmpi` installed and running on your machine.
In a new directory, here are the steps I took to create a virtual environment for this Jupyter notebook:
echo ""
echo "Preparing a virtual environment for NetPyN... | github_jupyter |
```
import numpy
import random
import math
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
address = ""
data = pd.read_csv(address); #To read csv file
df = pd.DataFrame(data)
df
#z-score normalization
df['signal_strength']=((df['signal_strength']-df['signa... | github_jupyter |
```
# Libraries needed for NLP
import nltk
nltk.download('punkt')
from nltk.stem.lancaster import LancasterStemmer
stemmer = LancasterStemmer()
# Libraries needed for Tensorflow processing
import tensorflow as tf
import numpy as np
import tflearn
import random
import json
from google.colab import files
files.upload()
... | github_jupyter |
## Predicting Missing links in a citation network
```
# global imports
import random
import numpy as np
import pandas as pd
import jgraph ## this was previously known as igraph
import csv
import matplotlib.pyplot as plt
# machine learning imports
from sklearn import svm
from sklearn.feature_extraction.text impor... | github_jupyter |
## Dependencies
```
import json, warnings, shutil, glob
from jigsaw_utility_scripts import *
from scripts_step_lr_schedulers import *
from transformers import TFXLMRobertaModel, XLMRobertaConfig
from tensorflow.keras.models import Model
from tensorflow.keras import optimizers, metrics, losses, layers
SEED = 0
seed_ev... | github_jupyter |
```
import pandas as pd
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
import pandas.util.testing as tm
from sklearn.preprocessing import LabelEncoder
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import ... | github_jupyter |
# 07.00 - Modeling - Prophet Model & Select Cross Validation Rolling Window Size
+ We have data for each summer from 1994 to 2018
+ We initially decided that the minimum size of the hold out test data is 5 years from 2014 to 2018
+ We want to select a rolling window that extracts as much value as possible fom the d... | github_jupyter |
**Aim: Implement Decsion Tree classifier**
- Implement Decision Tree classifier using scikit learn library
- Test the classifier for Weather dataset
Step 1: Import necessary libraries.
```
from sklearn import preprocessing
from sklearn.tree import DecisionTreeClassifier
```
Step 2: Prepare dataset.
```
#P... | github_jupyter |
https://fenderist.tistory.com/168
타자
AVG(Batting Average) : 타율
G (Game) : 참여경기수(경기)
PA(Plate Appearances) : 타석수( 타자가 타석에 선 횟수 ), 한게임 평균 3~4타석 슴
AB(At Bat) : 타수 ( 타격을 완료한 횟수, 볼넷, 희생번트, 타격 방해등은 포함 X)
R(Runs) : 득점 ( 홈플레이트를 밟아 팀에 점수가 올랐을때 기록됨 )
H(Hits) : 안타
2B(double) : 2루타
3B(Triple) : 3루타
HR(Home Run) : 홈런
TB(Total Bas... | github_jupyter |
# Linear Algebra Review
- **Scalar:** Any single numerical value.
- **Vector:** An array of numbers(data) is a vector.
- **Matrix:** A matrix is a 2-D array of shape (m×n) with m rows and n columns.
- **Tensor:** Generally, an n-dimensional array where n>2 is called a Tensor. But ... | github_jupyter |
## 1. 데이터 불러오기
```
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import random
data1 = pd.read_csv('C:/Users/Soyoung Cho/Desktop/NMT Project/dataset/train.csv')
data2 = pd.read_csv('C:/Users/Soyoung Cho/Desktop/NMT Project/dataset/test.csv')
data3 = pd.read_csv('C:/Users/Soyoung Cho/Desktop... | github_jupyter |
> **Tip**: Welcome to the Investigate a Dataset project! You will find tips in quoted sections like this to help organize your approach to your investigation. Before submitting your project, it will be a good idea to go back through your report and remove these sections to make the presentation of your work as tidy as ... | github_jupyter |
```
import data_loader as dl
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
np.random.seed(0)
train_df, valid_df = dl.load_train_data("adult.data")
test_df = dl.load_test_data("adult.test")
column_names = ['age', 'workclass', 'fnlwgt', 'education', 'education.num', 'martia... | github_jupyter |
```
#import all the dependencies
import os
import csv
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
#read the csv files to view the data
google_apps = pd.read_csv("googleplaystore.csv")
google_apps.shape
```
# Data Cleaning
```
#Check for number of apps in total
no_apps = google_apps["App"... | github_jupyter |
<center><h2>Assignment</h2></center>
<h3>2.1. Problem Statement: PYTHON 1</h3>
<b>1. Install Jupyter notebook and run the first program and share the screenshot of the output.</b>
```
str = "Hello Python. This is my First Program";
print(str);
```
<b>2. Write a program which will find all such numbers which are div... | github_jupyter |
###### ECE 283: Homework 2
###### Topics: Classification using neural networks
###### Due: Monday April 30
- Neural networks; Tensorflow
- 2D synthetic gaussian mixture data for binary classification
### Report
----------------------------------------
##### 1. Tensorflow based neural network
- 2D Gaussian mixture ... | github_jupyter |
```
import sys
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KDTree
from sklearn.decomposition import PCA
#### Visulization imports
import pandas_profiling
import plotly.express as px
import seaborn as sns
import p... | github_jupyter |
<a href="https://colab.research.google.com/github/Shaheer-Khan/AISem3/blob/master/HW/Home_Credit_default_risk_HW.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
!pip install xgboost
#data.set_index("SK_ID_CURR",
# drop=True,
# ... | github_jupyter |
# Measuring PROV Provenance on the Web of Data
* Authors:
* [Paul Groth](http://pgroth.com), [Elsevier Labs](http://labs.elsevier.com)
* [Wouter Beek](http://www.wouterbeek.com), Vrije Universiteit Amsterdam
* Date: May 11, 2016
One of the motivations behind the original charter for the [W3C Provenance Incub... | github_jupyter |
```
try:
# %tensorflow_version only exists in Colab.
%tensorflow_version 2.x
except Exception:
!pip install -q tensorflow-gpu>=2.0.0
!pip install --quiet neural-structured-learning
from __future__ import absolute_import, division, print_function, unicode_literals
import neural_structured_learning as nsl
import ... | github_jupyter |
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