text stringlengths 2.5k 6.39M | kind stringclasses 3
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Before you turn this problem in, make sure everything runs as expected. First, **restart the kernel** (in the menubar, select Kernel$\rightarrow$Restart) and then **run all cells** (in the menubar, select Cell$\rightarrow$Run All).
Make sure you fill in any place that says `YOUR CODE HERE` or "YOUR ANSWER HERE", as we... | github_jupyter |
# Homework 3 - Neural Network Post-Training Static Quantization
## STUDENT NAME: [full name here]
## STUDENT PURDUE USERNAME: [username here]
# Setup
> **TASKS:**
> 1. Run these cells to grab the PyPI packages and import the dependencies for the notebook. You can click into the "Files" explorer on the sidebar to conf... | github_jupyter |
Team Members
- Shubhendu Vimal - 11915067
- Dharani Kiran Kavuri - 11915033
- Anmol More - 11915043
<H2> ReadMe :</H2>
- Data Preparation through python script
- Convert raw data csv and then to libsvm in R
- Run spark ML algos in jupyter notebook
```
import pandas as pd
import glob
from pyspark.ml.classification... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
dt = np.dtype([('instance_no', int),
('exp_no', int),
('method', int), # 1 = white box, 2 = euclidean_PCA, 3 = hog, 4 = euclidean_PCA category, 5 = hog category, 6 = ais
('pca... | github_jupyter |
TSG037 - Determine master pool pod hosting primary replica
==========================================================
Description
-----------
Determine the pod that hosts the primary replica for the Big Data
Cluster when master pool high availability is enabled.
For BDC deployed with High availability, the master po... | github_jupyter |
<table class="ee-notebook-buttons" align="left">
<td><a target="_blank" href="https://github.com/giswqs/earthengine-py-notebooks/tree/master/FeatureCollection/extract_image_by_polygon.ipynb"><img width=32px src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" /> View source on GitHub</a></td>
<td><a ta... | github_jupyter |
## Dependencies
```
import os
import cv2
import shutil
import random
import warnings
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import imgaug as ia
from imgaug import augmenters as iaa
from sklearn.utils import class_weight, shuffle
from sklearn.model_selection import ... | github_jupyter |
## Uygulamalı Veri Bilimi ve Makine Öğrenimi Eğitim Kampı
### Kodluyoruz Ağustos-Eylül 2019 Ankara
### 3. hafta
Geçtiğimiz hafta istatistik temellerine değindik
Anahtar kelimeler:
* Z Table
* Normal dağılım (Gaussian) (çan)
* Uniform dağılım
* Poisson dağılımı
* Probability Density Function (PDF)
* Cumulative Dist... | github_jupyter |
```
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split, GridSearchCV
from matplotlib import pyplot as plt
import seaborn as sns
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from sklearn.linear_model import Ridge, Lasso, ElasticNet, LinearRegression
from sklea... | github_jupyter |
# Option pricing with the Heston / Hull White model
##The model
The Heston / Hull-White model is a Heston model, where the dynamic of the risk-free rate is governed by a Hull-White one-factor model:
\begin{align}
\frac{dS}{S}& = (r_t - \nu) dt + \sqrt{V_t} dZ_t \\
dV_t& = \kappa_V(\theta_V - V_t) dt + \sigma_V \sqrt... | github_jupyter |
Jupyter Notebooks
==================
A notebook consists in a set of cells. These cells are interpreted either as text instruction (i.e. **markdown**) or as Python **code**.
* Each cell can be edited using ``[Enter]`` key (i.e. *edit mode*). To return to the *navigation mode*, use the ``[Esc]`` key.
* To switch chan... | github_jupyter |
# MNIST keras model
This notebook is part of this [post](https://www.stupid-projects.com/machine-learning-on-embedded-part-1) which is part a series of post about using ML and NN in embedded MCUs.
I've taken this notebook has been taken from this github repo and just added a few stuff:
https://github.com/fchollet/dee... | github_jupyter |
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import preprocessing
from sklearn import metrics
import os, sys
from time import time
from phm08ds.models import experiment
```
## Load Dataset
```
folderpath = '../../../data/interim/'
data_op_05 = pd.read_csv(folderpath + 'dat... | github_jupyter |
## Scientific Python
### Matrices
Dealing with vectors and matrices efficiently requires the **numpy** library. For the sake of brevity we will import this with a shorter name:
```
import numpy as np
```
The numpy supports arrays and matrices with many of the features that would be familiar to matlab users. See here... | github_jupyter |
# Integration with Simpson's rule
In this notebook we look at a more efficient method for numerical integraiton: Simpon's rule
```
import numpy as np
import matplotlib.pyplot as plt
# The below commands make the font and image size bigger
plt.rcParams.update({'font.size': 22})
plt.rcParams["figure.figsize"] = (15,10)... | github_jupyter |
# JSON and HTML Processing
In this tutorial it is covered basic operations with HTML and JSON.
For more informations about related stuff see:
* <a href="https://en.wikipedia.org/wiki/JSON">JavaScript Object Notation</a>
* <a href="https://en.wikipedia.org/wiki/HTML">HyperText Markup Language (HTML)</a>
## HTML (XML) ... | github_jupyter |
```
# default_exp capture
```
# Capture
> Wrapper class and example code for getting images from the OpenHSI using a ximea detetor (with IMX252 sensor, e.g. MX031CG-SY).Wrapper class and example code for getting images from the OpenHSI using a ximea detetor (with IMX252 sensor, e.g. [MX031CG-SY](https://www.ximea.com... | github_jupyter |
# Deep Learning Bootcamp November 2017, GPU Computing for Data Scientists
<img src="../images/bcamp.png" align="center">
## Using CUDA, Jupyter, PyCUDA and PyTorch
### 01 PyCUDA verify CUDA 8.0
Web: https://www.meetup.com/Tel-Aviv-Deep-Learning-Bootcamp/events/241762893/
Notebooks: <a href="https://github.com/Quan... | github_jupyter |
# Process manager
The process manager allows the construction of sets of tasks to be run, which can be (but are not limited to) launch files or ROS nodes to bring up a system that may include an instance of Gazebo.
Each instance of the process manager can be set with a different `ROS_MASTER_URI` and `GAZEBO_MASTER_URI... | github_jupyter |
## Demonstrating the Workflow of the Online_IO Class: Implicit Update
### Stephanie Allen, *AMSC PhD, UMD-College Park*
We will demonstrate through the Markdown and code blocks below the workflow of the `Online_IO` class for the `Dong_implicit_update` option. We will be replicating an experiment from Dong, Chen, & ... | github_jupyter |
```
from google.colab import drive
drive.mount('/content/gdrive')
import os
os.chdir('/content/gdrive/My Drive/finch/tensorflow1/multi_turn_rewrite/chinese/main')
%tensorflow_version 1.x
!pip install texar
import tensorflow as tf
import texar.tf as tx
import numpy as np
import pprint
import logging
from pathlib impor... | github_jupyter |
<a href="https://colab.research.google.com/github/parament-integrator/examples/blob/master/Convergence_Plot.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Convergence plot
In this example we will recreate the convergence plot from our paper.
A ... | github_jupyter |
##### Copyright 2021 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 |
# BadSensorFinder Demo - Plotting the SVM Hyperplane
```
import os
os.chdir('../optidrift/')
import badsensorfinder
import pickle
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import pandas as pd
import matplotlib.pyplot as plt
import getdata
%matplotlib inline
```
## Build the model you want to plot the... | github_jupyter |
# Blockdiag Package Diagrams
The [`blockdiag`](http://blockdiag.com/en/) package provides tools for generating several types of diagram, from simple box and arrows diagrams to various diagrams familiar to communications and system engineers.
The diagrams are defined using simple text structures. Various IPython block... | github_jupyter |
# Simple Time Series Example
This tutorial shows how a simple time series simulation is performed with the timeseries and control module in pandapower. A time series calculation requires the minimum following inputs:
* pandapower net
* the time series (in a pandas Dataframe for example)
First we need some imports. Sp... | github_jupyter |
```
import glob
import pandas as pd
import os
import csv
import matplotlib.pyplot as plt
from scipy.stats import norm, kstest, shapiro, ranksums
import numpy as np
from itertools import combinations
```
# Gets Data
```
#store all data, from all configs, in a dict with key config and value dataframe converted to dict ... | github_jupyter |
```
# Remember: library imports are ALWAYS at the top of the script, no exceptions!
import sqlite3
import os
import pandas as pd
import numpy as np
from datetime import datetime
from sklearn.impute import KNNImputer
from pandas_profiling import ProfileReport
```
# Context
The data we will be using through the pratical... | github_jupyter |
# 7.6 Transformerモデル（分類タスク用）の実装
- 本ファイルでは、クラス分類のTransformerモデルを実装します。
※ 本章のファイルはすべてUbuntuでの動作を前提としています。Windowsなど文字コードが違う環境での動作にはご注意下さい。
# 7.6 学習目標
1. Transformerのモジュール構成を理解する
2. LSTMやRNNを使用せずCNNベースのTransformerで自然言語処理が可能な理由を理解する
3. Transformerを実装できるようになる
# 事前準備
書籍の指示に従い、本章で使用するデータを用意します
```
import math
import num... | github_jupyter |
```
import SimpleITK as sitk
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math
from scipy import signal
from numpy import *
from pylab import *
import cv2
import random
from random import randrange
from numpy import linalg
from scipy import signal
from pylab import *
from PIL import... | github_jupyter |
# Python for Environmental Science Day 3
## Topics
* Functions in Python
* Catching Errors in Python
## What the heck is a function?
Functions are time savers. A good programmer is a lazy programmer. If you have the possibility to not write something, it is usually a good idea to do so. And this is where functions com... | github_jupyter |
<center>
<img src="https://habrastorage.org/web/677/8e1/337/6778e1337c3d4b159d7e99df94227cb2.jpg"/>
## Специализация "Машинное обучение и анализ данных"
<center>Автор материала: программист-исследователь Mail.Ru Group, старший преподаватель Факультета Компьютерных Наук ВШЭ Юрий Кашницкий
# <center> Capstone проект №1.... | github_jupyter |
# Sphere function, vectorized
In the previous example, we solved the constrained Rosenbrock problem. This was a 2-dimensional problem, so we created two variables: $x$ and $y$.
However, imagine we had a problem with 100 variables. It'd be pretty tedious to create these variables individually and do the math on each v... | github_jupyter |
# Test instantiating PypIt parameter sets
```
# import
import os
from configobj import ConfigObj
from pypit.par import pypitpar
```
## General usage
```
# To get the default parameters, declare the parameters set
# without arguments
p = pypitpar.ProcessImagesPar()
# Use print() to get a short-form representation
pri... | github_jupyter |
```
try:
import settings
assert type(settings.CENSUS_KEY) == str or type(settings.CENSUS_KEY) == unicode
except Exception as e:
print ("error in importing settings to get at settings.CENSUS_KEY", e)
from census import Census
from us import states
c = Census(settings.CENSUS_KEY)
```
Does the `census` modul... | github_jupyter |
.. meta::
:description: A guide which introduces the most important steps to get started with pymoo, an open-source multi-objective optimization framework in Python.
.. meta::
:keywords: Multi-objective Optimization, Python, Evolutionary Computation, Optimization Test Problem, Hypervolume
## Getting Started
In... | github_jupyter |
# Learn to manage data collections using the generic list type
*This tutorial teaches you C# interactively, using your browser to write C# code and see the results of compiling and running your code. It contains a series of lessons that create, modify, and explore collections and arrays.*
## Create lists
Run the fol... | github_jupyter |
# Sparse Approximations
The `gp.MarginalSparse` class implements sparse, or inducing point, GP approximations. It works identically to `gp.Marginal`, except it additionally requires the locations of the inducing points (denoted `Xu`), and it accepts the argument `sigma` instead of `noise` because these sparse approx... | github_jupyter |
<a href="https://colab.research.google.com/github/Shahid-coder/python-colab/blob/main/04_list_and_tuples_methods.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# List methods
Lists are used to store multiple items in a single variable.
Lists are ... | github_jupyter |
# Computational Astrophysics
## Partial Differential Equations. 06
## Multidimensional Advection Equation
---
## Eduard Larrañaga
Observatorio Astronómico Nacional\
Facultad de Ciencias\
Universidad Nacional de Colombia
---
### About this notebook
In this notebook we present some of the techniques used to solve th... | github_jupyter |
# The Basics: Variables and Printing
This notebook is based on materials kindly provided by the [IN1900]( https://www.uio.no/studier/emner/matnat/ifi/IN1900/h19/) team.
Programming is a way of telling the computer what to do.
Computer programs are a kind of recipe, like cooking or knitting recipes.
However, cooking r... | github_jupyter |
```
#@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 writing, software
# distributed u... | github_jupyter |
```
import numpy as np
import os
from scipy.spatial.transform import Rotation as R
from sys import argv, exit
np.random.seed(42)
np.set_printoptions(formatter={'float': lambda x: "{0:0.5f}".format(x)})
def frobNorm(P1, P2, str1="mat1", str2="mat2"):
np.set_printoptions(suppress=True)
val = np.linalg.norm(P1 ... | github_jupyter |
# Numpy (Часть 3)
> 🚀 В этой практике нам понадобятся: `numpy==1.21.2`
> 🚀 Установить вы их можете с помощью команды: `!pip install numpy==1.21.2`
# Содержание <a name="content"></a>
* [Broadcasting (трансляция)](#Broadcasting_(transljatsija))
* [Изменение размеров массива (Reshape)](#Izmenenie_razmerov_massiva_... | github_jupyter |
```
!nvidia-smi
!pip --quiet install transformers
!pip --quiet install tokenizers
from google.colab import drive
drive.mount('/content/drive')
!cp -r '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Scripts/.' .
COLAB_BASE_PATH = '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/'
M... | github_jupyter |
```
%pylab inline
from parcels import FieldSet, Field, ParticleSet, JITParticle, AdvectionRK4, ErrorCode, Variable
import matplotlib.patches as mpatches
import cartopy
from datetime import timedelta as delta
import matplotlib.pyplot as plt
from glob import glob
import numpy as np
import xarray as xr
from os import envi... | github_jupyter |
```
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import base
LENGTH = 30
def lengths_of_searches():
grouped_users = base.get_dataset_and_group_by_user()
each_user_lengths_success = {}
each_user_lengths_fail = {}
for username, group in grouped_users:
this_user_length_su... | github_jupyter |
# Lagrangian mechanics in generalized coordinates
> Marcos Duarte
> Laboratory of Biomechanics and Motor Control ([http://demotu.org/](http://demotu.org/))
> Federal University of ABC, Brazil
## Generalized coordinates
The direct application of Newton's laws to mechanical systems results in a set of equations of... | github_jupyter |
# TIME SERIES IN LSTM
### ILLUSTRATION WITH SINE AND COS FUNCTIONS
```
%matplotlib inline
import numpy as np
from matplotlib import pyplot as plt
#from tensorflow.nn.rnn import *
from tensorflow.python.ops import *
%load_ext autoreload
%autoreload 2
import numpy as np
import pandas as pd
import tensorflow as tf
fro... | github_jupyter |
```
import sys
sys.path.append("/Users/sklim/Projects/DamGeophysics/codes/")
from Readfiles import getFnames
from DCdata import readReservoirDC
#from SimPEG import DCIP as DC
#from SimPEG import TDEM
from SimPEG.EM.Static import DC
from SimPEG import EM
from SimPEG import Mesh, Utils
%pylab inline
fname = "/Users/skli... | github_jupyter |
# Identify Worker Labeling Efficiency using SageMaker GroundTruth
### Introduction
Welcome to our example on identifying worker labeling efficiency for a SageMaker GroundTruth Labeling job. Before running this notebook, please make sure that all the instructions prior to the section 'Setup the Automated Accuracy Logic... | github_jupyter |
Before you turn this problem in, make sure everything runs as expected. First, **restart the kernel** (in the menubar, select Kernel$\rightarrow$Restart) and then **run all cells** (in the menubar, select Cell$\rightarrow$Run All).
Make sure you fill in any place that says `YOUR CODE HERE` or "YOUR ANSWER HERE", as we... | github_jupyter |
## Setup Data Fetching
```
import ta
import pandas as pd
import tensortrade.env.default as default
from tensortrade.data.cdd import CryptoDataDownload
from tensortrade.feed.core import Stream, DataFeed, NameSpace
from tensortrade.oms.instruments import USD, BTC, ETH, LTC
from tensortrade.oms.wallets import Wallet, P... | github_jupyter |
## Comparison between the iterative Image Space Restoration Algorithm (ISRA) and the Richardson-Lucy Algorithm (RLA)
Using the generated Voigt functions
```
#required libraries
%matplotlib qt
import numpy as np
import hyperspy.api as hs
from ncempy.io import dm
import matplotlib.pyplot as plt
from scipy.signal import... | github_jupyter |
```
%matplotlib inline
```
# Balance model complexity and cross-validated score
This example balances model complexity and cross-validated score by
finding a decent accuracy within 1 standard deviation of the best accuracy
score while minimising the number of PCA components [1].
The figure shows the trade-off betw... | github_jupyter |
# Get table and use a function to convert to dates
## Example bankruptcies
This weekly StatBank table has a break in the time series from 2010-2018.It is suitable for displaying the date conversion function. Here figures are shown both with the x-axis as categories and as date.
Source: [12972](https://www.ssb.no/en/st... | github_jupyter |
```
import torch
from torch import nn, optim
from torch.utils.data import DataLoader, Dataset
from torchvision import datasets, transforms
from torchvision.utils import make_grid
from matplotlib import pyplot as plt
import seaborn as sns
from IPython import display
import numpy as np
from PIL import Image
import torchm... | github_jupyter |
Hurricane Tracker with NHC Data
===============================
By: Aodhan Sweeney
This program is a recreation of the 2014 hur_tracker.py
originally written by Unidata Intern Florita Rodriguez. The
2019 version comes with updated interface and functionality,
as well as changing certain dependencies.
```
import gzip... | github_jupyter |
<a name="top"></a><img src="images/chisel_1024.png" alt="Chisel logo" style="width:480px;" />
# Module 4.4: A FIRRTL Transform Example
**Prev: [Common Pass Idioms](4.3_firrtl_common_idioms.ipynb)**<br>
This AnalyzeCircuit Transform walks a `firrtl.ir.Circuit`, and records the number of add ops it finds, per module.
... | github_jupyter |
<a href="https://colab.research.google.com/drive/1KrMIELsuGSoTdT5pV2CBUCulArgbGjGc?authuser=1#scrollTo=hMypMs2KDmK3">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
## 1. Google Play Store apps and reviews
<p>Mobile apps are everywhere. They are easy to create and can ... | github_jupyter |
### IMPORTS
```
import cv2
import numpy as np
import time
from collections import deque
import img2pdf
import os
import glob
```
### CONSTANTS
```
# Colors
colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255)]
counter = 0
PATH = r"C:/Users/rajat/Desktop/" # Where to save ?
# Define the upper and lower boundaries for a... | github_jupyter |
```
%matplotlib notebook
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import requests
import time
import random
from scipy import stats
pop_data = pd.read_csv('../Inputs/POPSTATSInputs/population_estimates_project1.csv')
pop_data
pop_data = pop_data.loc[[2, 6, 38, 48]]
pop_data
pop_data = pop_... | github_jupyter |
**Chapter 16 – Natural Language Processing with RNNs and Attention**
_This notebook contains all the sample code in chapter 16._
<table align="left">
<td>
<a target="_blank" href="https://colab.research.google.com/github/rickiepark/handson-ml2/blob/master/16_nlp_with_rnns_and_attention.ipynb"><img src="https://... | github_jupyter |
# Assingment 1 - Malaria Cell Image Classification
### Course: Convolutional Neural Networks with Applications in Medical Image Analysis
Office hours: Alternating weeks on Thursdays 13.15--16.00 (Minh) and Wednesdays 08.15--12.00 (Attila). See the course web page for details and potential changes.
The first assignmen... | github_jupyter |
### Baseline model (returns the survived value based on its probability in training data set)
##### Import processed training data for baseline model
```
import pandas as pd
import numpy as np
import os as os
import sklearn
processed_dir_path=os.path.join(os.pardir,"data", "processed")
processed_data_path=os.path.joi... | github_jupyter |
## Quick check of target preference profiles and corrsponding utility space
```
## pip install git+https://github.com/SifanSong/trackgenius.git
import numpy as np
%matplotlib inline
## only Background required to be imported
from trackgenius.utilities.background import Background
## Basic configuration
## DOMAIN_Pa... | github_jupyter |
<table align="center">
<td align="center"><a target="_blank" href="http://introtodeeplearning.com">
<img src="http://introtodeeplearning.com/images/colab/mit.png" style="padding-bottom:5px;" />
Visit MIT Deep Learning</a></td>
<td align="center"><a target="_blank" href="https://colab.research.google.c... | github_jupyter |
# Multi Layer Perceptron - PyTorch
* load mnist data set
* define network
* set loss and optimiser
* train and validate
```
import torch
import numpy as np
from torchvision import datasets # to load mnist dataset
import torchvision.transforms as transforms # dataset transformations such as totensor
num_workers = 0
ba... | github_jupyter |
# Color cycle analysis
The training process takes several hours.
```
import csv
import gzip
import itertools
import logging
import os
import random
import shutil
import sqlite3
import sys
import time
import numpy as np
import colorspacious
from tensorflow.keras.models import Model
from tensorflow.keras.layers import ... | github_jupyter |
```
import os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torch.autograd import Variable
import torchvision.transforms as transforms
from torchvision.utils import save_image
from torchvision import datasets
num_eps=10
bsize=32
lra... | github_jupyter |
# Exercise Set 3: Strings, requests and APIs
*Morning, August 13, 2019*
In this exercise set you will be working with collecting from the web. We will start out with some basic string operations and build on that to make a query for fetching data.
In addition to DataCamp, you might find [this page](https://pythonpro... | github_jupyter |
```
import collections
import glob
import re
import tarfile
import math
from pprint import pprint
import os
import spacy
import pandas as pd
from collections import Counter
def read_archive(path):
tar = tarfile.open(path, "r:gz")
files = {}
for filename in tar.getnames():
f = tar.extractfile(file... | github_jupyter |
<table style="border: none" align="left">
<tr style="border: none">
<th style="border: none"><font face="verdana" size="4" color="black"><b>Use Spark ML and Python to detect network intrusions</b></font></th>
<th style="border: none"><img src="https://github.com/pmservice/customer-satisfaction-prediction... | github_jupyter |
```
import requests
import pandas as pd
from bs4 import BeautifulSoup
# if we did no have requests then we would install it manually:
# !pip install requests from Jupyter notebook
# pip install requests from command line
url = "https://www.ss.com/lv/real-estate/wood/"
req = requests.get(url)
req.status_code
len(req.tex... | github_jupyter |
# Foundations of Computational Economics #27
by Fedor Iskhakov, ANU
<img src="_static/img/dag3logo.png" style="width:256px;">
## Dynamic programming in discrete world
<img src="_static/img/lecture.png" style="width:64px;">
<img src="_static/img/youtube.png" style="width:65px;">
[https://youtu.be/kpNGDQnDpmU](http... | github_jupyter |
<a href="https://colab.research.google.com/github/shridharshukla/TSF_DataScienceAndBusinessAnalytics_II/blob/main/Task_2_KMeans_Clustering.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Prediction using Unsupervised ML
### Workshop - 1: K- Means... | github_jupyter |
<a href="https://colab.research.google.com/github/IsraelAbebe/Personal-Projects-and-Exercises/blob/master/AIMS-Assignments/Deep-Learning/ExerciseOne.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
import torch
```
# Question 1
```
a = torch.fu... | github_jupyter |
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error
from sklearn.metrics import mean_absolute_error
import joblib
import tensorflow as tf
import math
pd.set_option('display.max_rows', 10000)
%matplo... | github_jupyter |
# Classifying Fashion-MNIST
Now it's your turn to build and train a neural network. You'll be using the [Fashion-MNIST dataset](https://github.com/zalandoresearch/fashion-mnist), a drop-in replacement for the MNIST dataset. MNIST is actually quite trivial with neural networks where you can easily achieve better than 9... | github_jupyter |
```
####################################################################################################
# Copyright 2019 Srijan Verma and EMBL-European Bioinformatics Institute
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License... | github_jupyter |
***
# 数据清洗：
> # 对占中新闻进行数据清洗
***
***
王成军
wangchengjun@nju.edu.cn
计算传播网 http://computational-communication.com
```
# 使用with open读取每一行数据
with open("/Users/chengjun/github/cjc/data/occupycentral/zz-hk-2014-10.rtf") as f:
news = f.readlines()
# 查看总共有多少行
len(news)
# 注意：标题和版面之间存在一个空行！所以title是block的第4个元素。
for i in rang... | github_jupyter |
# Introduction
In this article, we show how to represent basic poker elements in Python, e.g., Hands and Combos, and how to calculate poker odds, i.e., likelihood of win/tie/lose in No-Limit Texas Hold'em.
We provide a practical analysis based on a real story in a *Night at the Venetian*.
We will use the package **p... | github_jupyter |
# A few notes on tensor operations in numpy
To calculate the "convolution" operation defined by the lecture note, which is indeed more often referred as cross-correlation, can be done with the function `signal.correlate2d` in `scipy`.
```
import numpy as np
from scipy import signal
a = np.arange(9).reshape((3,3))
b = ... | github_jupyter |
# Practice Exercise Linear Regression
## We will be using the Boston house price dataset for this exercise.
#### This dataset is in-built in Python in the Sci-kit learn library. But for this exercise, we have already downloaded this dataset in the form of a csv file.
**Importing Libraries**
```
from sklearn.datasets... | github_jupyter |
```
%load_ext Cython
%%cython
from pycalphad.core.rksum import RedlichKisterSum
from pycalphad import Database
cimport numpy as np
import numpy as np
from tinydb import where
from sympy import Symbol
cdef np.ndarray[ndim=1, dtype=np.float64_t] _eval_rk_matrix_gradient(double[:,:] coef_mat, double[:,:] symbol_mat,
... | github_jupyter |
https://discourse.julialang.org/t/help-to-get-my-slow-julia-code-to-run-as-fast-as-rust-java-lisp/65741
```
# download dictionary
if !isfile("dictionary.txt")
dictionary_url = "https://raw.githubusercontent.com/renatoathaydes/prechelt-phone-number-encoding/julia/dictionary.txt"
Downloads.download(dictionary_ur... | github_jupyter |
```
%%capture
from dask_jobqueue import SLURMCluster
from dask.distributed import Client
import xarray as xr
import os
import gsw
import time
import numpy as np
import pandas as pd
from scipy.interpolate import interp1d, PchipInterpolator
cluster = SLURMCluster(queue='any2', cores=24, memory='48GB', processes=2)
cluste... | github_jupyter |
## Variational Inference
The dataset required is small and is available preprocessed here:
- https://drive.google.com/drive/folders/1Tg_3SlKbdv0pDog6k2ys0J79e1-vgRyd?usp=sharing
```
import torch
import numpy as np
from gpytorch.optim import NGD
from torch.optim import Adam
from torch.nn import Parameter
from matplot... | github_jupyter |
# Example of use
```
import LMIPy
LMIPy.__version__
```
## Collection objects: Searching
If you don't know what data you are interested in advance, you can search by keywords and return a list of objects.
```
c = LMIPy.Collection('tree cover', object_type=['layer','dataset'], app=['gfw'], limit=10)
c
```
Searching... | github_jupyter |
# Simple data exploration
In this notebook we will explore a dataset from an article by a team at autodesk (which I link to below).
We can think of this as the simple data exploration you might do when you first start working with a new dataset.
First, we will load pandas and numpy, and read the comma-separated-value... | github_jupyter |
```
%matplotlib inline
from os import listdir
from os.path import isfile, join
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.optimizers import Adam
from keras.layers.normali... | github_jupyter |
# Exercise 3: Parallel ETL
```
%load_ext sql
from time import time
import configparser
import matplotlib.pyplot as plt
import pandas as pd
```
# STEP 1: Get the params of the created redshift cluster
- We need:
- The redshift cluster <font color='red'>endpoint</font>
- The <font color='red'>IAM role ARN</fon... | github_jupyter |
<a href="https://colab.research.google.com/github/Tessellate-Imaging/monk_v1/blob/master/study_roadmaps/1_getting_started_roadmap/2_elemental_features_of_monk/1)%20Feature%20-%20Experiment%20Summaries.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
... | github_jupyter |
# SQLクエリによるデータの取得 🐇
このノートブックでは SELECT 文を使ったデータの取得方法について確認していきます。
## 1. 初期設定
Jupyter Notebook を再起動した場合などはここから実行してください
```
! pip install ipython-sql pymysql
%load_ext sql
```
## 2. 接続確認
```
%%sql mysql+pymysql://hello:world@10.0.1.100/employees
select 'hello' as world
```
## 3. テーブル構成の調査
まずはどんなテーブルが存在するか調べてみましょう。... | github_jupyter |
```
%load_ext autoreload
%autoreload 2
%matplotlib inline
import sys
sys.path.insert(0, '../')
import numpy as np
import tensorflow as tf
import functools
from matplotlib import pyplot as plt
import os
os.environ["CUDA_VISIBLE_DEVICES"]="1"
from gantools import utils, plot
from gantools.gansystem import GANsystem
from... | github_jupyter |
```
import numpy
from scipy import ndimage
import pandas
from geoh5 import kea
from geoh5.kea import common as kc
# https://github.com/sixy6e/image-processing
from image_processing.segmentation import Segments
```
In this example we'll create a segmented array, and compute some basic statistics for every segment
(min... | github_jupyter |
# 5. Joining Tables
This is the fifth in a series of notebooks related to astronomy data.
As a continuing example, we will replicate part of the analysis in a recent paper, "[Off the beaten path: Gaia reveals GD-1 stars outside of the main stream](https://arxiv.org/abs/1805.00425)" by Adrian M. Price-Whelan and Ana B... | github_jupyter |
```
# import libraries
import torch
import torch.nn as nn
import torch.optim as optim
import torchvision
import torchvision.transforms as transforms
import numpy as np
from torch.utils.data.sampler import SubsetRandomSampler
from torch.utils.tensorboard import SummaryWriter
from utils import device, get_num_correct, ... | github_jupyter |
# LOCCNet: A Machine Learning Framework for LOCC Protocols
<em> Copyright (c) 2021 Institute for Quantum Computing, Baidu Inc. All Rights Reserved. </em>
## Overview
Quantum entanglement is an essential physical resource for quantum communication, quantum computation, and many other quantum technologies. Therefore, ... | github_jupyter |
##### Copyright 2020 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 |
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