text stringlengths 2.5k 6.39M | kind stringclasses 3
values |
|---|---|
```
!git clone https://github.com/NVlabs/stylegan3.git
!pip install --upgrade psutil
# based on https://github.com/Sxela/stylegan3_blending/blob/main/stylegan3_blending_public.ipynb
import os
import sys
sys.path.append(os.path.join(os.path.abspath(""), "stylegan3"))
import copy
import math
import pickle
from glob impo... | github_jupyter |
<table>
<tr><td align="right" style="background-color:#ffffff;">
<img src="../images/logo.jpg" width="20%" align="right">
</td></tr>
<tr><td align="right" style="color:#777777;background-color:#ffffff;font-size:12px;">
Abuzer Yakaryilmaz | April 04, 2019 (updated)
</td></tr>
<tr><td... | github_jupyter |
# Policy Gradient (PG)
Referências:
- [Schulman, John. _Optimizing Expectations_: From Deep Reinforcement Learning to Stochastic Computation Graphs](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-217.html).
- [Spinning Up](https://spinningup.openai.com/en/latest/spinningup/rl_intro3.html)
# Conceito
Em t... | github_jupyter |
# Introduction to Programming with Python
# Unit 4: Loops
Our task of generating a problem book with quadratic equations will only be useful, if we can generate many equations of the same type, not just one. Computer is very good at repeating the same computations, so the ability for us to express the idea of repeati... | github_jupyter |
# Aerospike Java Client – Advanced Collection Data Types
*Last updated: June 22, 2021*
The goal of this tutorial is to highlight the power of working with [collection data types (CDTs)]("https://docs.aerospike.com/docs/guide/cdt.html") in Aerospike. It covers the following topics:
1. Setting [contexts (CTXs)]("https:/... | github_jupyter |
# Assignment 3 - Practical Deep Learning Workshop
#### In this task we will work with the dataset of the Home depot product search relevance competition.
#### Some background:
In this competition, Home Depot is asking to help them improve their customers' shopping experience by developing a model that can accurately ... | github_jupyter |
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-59152712-8"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'UA-59152712-8');
</script>
# $\texttt{GiRaFFE}$: General Relativistic Force-Free Elect... | github_jupyter |
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT License.
* リスト、タプル、辞書
* numpy
## Jupyter notebookことはじめ
コードの編集：各セルをクリックして、その中で直接編集
コードの実行：画面上の再生ボタンをクリックまたはShift+Enter
実行停止：画面上の停止ボタンをクリック
Note... | github_jupyter |
# 6.1 Reading and Writing Data in Text Format
```
import pandas as pd
import numpy as np
df = pd.read_csv('datasets/ex1.csv')
df
df = pd.read_table('datasets/ex1.csv', sep=',')
df
pd.read_csv('datasets/ex2.csv', header=None)
pd.read_csv('datasets/ex2.csv', names=['a', 'b', 'c', 'd', 'message'])
names = ['a', 'b', 'c',... | github_jupyter |
## Overview - Business Understanding
In this notebook, I would like to explore the educational and job satisfaction characteristics of respondents of the survey based in Nigeria. To achieve this, I will retrieve data from the Stackoverflow developer survey 2017. The questions that I am interested in asking are;
- Wha... | github_jupyter |
<h2>Grover's Search: One Qubit Representation</h2>
[Watch Lecture](https://youtu.be/VwzshIQsDBA)
The execution of Grover's search algorithm can be simulated on the unit circle.
Throughout the computation, the amplitudes of the marked (or unmarked) elements never differ from each other. Therefore, we can group the e... | 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 pool has at least
three master PODs (availablity group replicas), SQ... | github_jupyter |
```
import keras
print(keras.__version__)
#Importing Libraries
import sys
import os
import numpy as np
import pandas as pd
from tensorflow.keras import Sequential
from keras.layers import Dense,Dropout,Activation,Flatten
from keras.layers import Conv2D,MaxPooling2D,BatchNormalization,AveragePooling2D
from keras.losses ... | github_jupyter |
# Text
*Under construction*
<!--
## Strings
[Strings](https://docs.python.org/3/library/stdtypes.html#text-sequence-type-str) are defined using (single or double) quotes:
```python
mathematician = 'Ramanujan'
print(mathematician)
```
Ramanujan
A [string](https://docs.python.org/3/library/stdtypes.html#text-... | github_jupyter |
# Lab 04 : Test set evaluation -- demo
```
# For Google Colaboratory
import sys, os
if 'google.colab' in sys.modules:
from google.colab import drive
drive.mount('/content/gdrive')
file_name = 'test_set_demo.ipynb'
import subprocess
path_to_file = subprocess.check_output('find . -type f -name ' + st... | github_jupyter |
# What is Survival Analysis?
[Survival analysis](https://en.wikipedia.org/wiki/Survival_analysis) is used to study the **time** until some **event** of interest (often referred to as **death**) occurs. Time could be measured in years, months, weeks, days, etc. The event could be anything of interest. It could be an... | github_jupyter |
# Import Modules
```
import os
print(os.getcwd())
import sys
import pandas as pd
import numpy as np
from pymatgen.io.ase import AseAtomsAdaptor
# #########################################################
from methods import get_df_dft
# #########################################################
# from local_method... | github_jupyter |
<i>Copyright (c) Microsoft Corporation.</i>
<i>Licensed under the MIT License.</i>
# ARIMA: Autoregressive Integrated Moving Average
This notebook provides an example of how to train an ARIMA model to generate point forecasts of product sales in retail. We will train an ARIMA based model on the Orange Juice dataset.... | github_jupyter |
# Assignment Algorithms : Part 1
The purpose of this notebook is to explore the fiberassign algorithms and the consequences of introducing different target populations and realistic nominal positioner motions and exclusion zones. Very often people see behavior of the fiberassign code which does not match their intuit... | github_jupyter |
```
# Necessary imports
import pylab as py
import numpy as np
import qiskit as qk
from qiskit import Aer
from qiskit import assemble
from scipy.linalg import eigvalsh, eigh
# Define the Pauli matrices here to reduce dependencies on other packages
X = np.array([[0,1],[1,0]],dtype=float)
Z = np.array([[1,0],[0,-1]],dty... | github_jupyter |
# 1Strategy ML Immersion Day
### Building an xgboost model from movie data
```
import json
import math
import sys
import boto3
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import sagemaker as sm
from sagemaker.amazon.amazon_estimator import get_image_uri
import workshop_utils as wu
# preve... | github_jupyter |
<a href="https://colab.research.google.com/github/Sparrow0hawk/crime_sim_toolkit/blob/crime_cat_refac/data_manipulation/Forces_%2B_LSOAs.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Generate a reference document matching LSOAs to Police Force c... | github_jupyter |
# Sensitivity Tests Output
```
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import pandas as pd
import os
from tqdm import tqdm
from pathlib import Path
import photoeccentric as ph
from pathlib import Path
plt.rcParams['figure.dpi'] = 150
def rmdir(directory):
directory = Path(director... | github_jupyter |
# DoWhy: Different estimation methods for causal inference
This is a quick introduction to the DoWhy causal inference library.
We will load in a sample dataset and use different methods for estimating the causal effect of a (pre-specified)treatment variable on a (pre-specified) outcome variable.
First, let us add the ... | github_jupyter |
# Jouer avec les mots
Les mots utilisés dans ce chapitre sont des mots français pour le Scrabble de Jean-Philippe Durand, disponible sous http://jph.durand.free.fr/scrabble.txt
Le document est sauvegardé localement sous le nom `mots.txt`.
## Lire des listes de mots
La première action est de créer une objet `fichier... | github_jupyter |
```
#!/usr/bin/env python3
"""feature_vectors.ipynb
James Gardner 2019
reads in TGSS and NVSS sources in a 20° patch of sky
and computes positional matches within 10'
adds labels based off of positional matching
requires the unzipped catalogues to be present in cwd
and expects names: TGSSADR1_7sigma_catalog.tsv and C... | github_jupyter |
# Cross-Validation and the Test Set
In the last lecture, we saw how keeping some data hidden from our model could help us to get a clearer understanding of whether or not the model was overfitting. This time, we'll introduce a common automated framework for handling this task, called **cross-validation**. We'll also i... | github_jupyter |
```
from z3 import *
import numpy as np
from itertools import combinations
from typing import Sequence
from tqdm.notebook import tqdm
```
Read instance file:
```
input_filename = '../../Instances/12x12.txt'
w, h, n, DX, DY = None, None, None, None, None
with open(input_filename, 'r') as f_in:
lines = f_in.read(... | github_jupyter |
```
import sys
sys.path.append("..")
import pandas as pd
import numpy as np
from numba import jit
import json
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import xmltodict
import numpy.polynomial as p
from multiprocessing import Pool
import time
from datetime import datetime , date, timedelt... | github_jupyter |
# Report for yuvipanda
```
import seaborn as sns
import pandas as pd
import numpy as np
import altair as alt
from markdown import markdown
from IPython.display import Markdown
from ipywidgets.widgets import HTML, Tab
from ipywidgets import widgets
from datetime import timedelta
from matplotlib import pyplot as plt
imp... | github_jupyter |
```
import pandas as pd
import datetime as dt
```
# testing it
## Review of Python's `datetime` Module
```
someday = dt.date(2010, 1, 20)
someday.year
someday.month
someday.day
str(someday)
str(dt.datetime(2010, 1, 10, 17, 13, 57))
sometime = dt.datetime(2010, 1, 10, 17, 13, 57)
sometime.year
sometime.month
some... | github_jupyter |
# The Basic Tools of the Deep Life Sciences
Welcome to DeepChem's introductory tutorial for the deep life sciences. This series of notebooks is a step-by-step guide for you to get to know the new tools and techniques needed to do deep learning for the life sciences. We'll start from the basics, assuming that you're ne... | github_jupyter |
# stockmanager
stockmanager has the following main modules:
- Ticker: a class to retrieve price, company info of a ticker.
- visualization: a set of visualization functions, e.g. plot_price()
- Portfolio: a class
```
from stockmanager import Ticker, Portfolio, plot_price
# For debugging:
import matplotlib.pyplot a... | github_jupyter |
# Naive Bayes Classifiers
We want to classify vectors of discrete value features, $\mathbf{x}\in\{1,\ldots,K\}^D$, where $K$ is the number of values for each feature, and $D$ is the number of features. If we use a generative approach, we will need to specify the class conditional distribution $p(\mathbf{x}|y=c), c\in\... | github_jupyter |
### Лекция 5. Шаблоны
<br />
##### Какая идея стоит за шаблонами
Ранее мы познакомились с возможностью перегрузки функций. Давайте вспомним её на примере swap:
```c++
// поменять местами два int
void my_swap(int& a, int& b)
{
int tmp = a;
a = b;
b = tmp;
}
// поменять местами два short
void my_swap... | github_jupyter |
# Lista 01 - EDA + Visualização
```
# -*- coding: utf 8
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
plt.style.use('seaborn-colorblind')
plt.ion()
```
# Exercício 01:
Em determinadas épocas do ano a venda de certos produtos sofre um aumento significativo. Um exemplo disso, são as ven... | github_jupyter |
```
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
# Plot parameters
sns.set()
%pylab inline
pylab.rcParams['figure.figsize'] = (4, 4)
plt.rcParams['xtick.major.size'] = 0
plt.rcParams['ytick.major.size'] = 0
# Avoid inaccurate floating values (for inverse matrices in dot product for instance)... | github_jupyter |
##### Copyright 2020 The TensorFlow IO 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 ... | github_jupyter |
# Process specifications
Dynamically adjusting parameters in a process to meet a specification is critical in designing a production process, and even more so when its under uncertaintly. BioSTEAM groups process specifications into two categories: analytical specifications, and numerical specifications. As the name su... | github_jupyter |
# 3.1 Expressions #
Programming languages are much simpler than human languages. Nonetheless, there are some rules of grammar to learn in any language, and that is where we will begin. In this text, we will use the [Python](https://www.python.org/) programming language. Learning the grammar rules is essential, and the ... | github_jupyter |
```
import arviz as az
import matplotlib.pyplot as plt
import numpy as np
import pymc3 as pm
%load_ext watermark
az.style.use('arviz-darkgrid')
```
# Sequential Monte Carlo - Approximate Bayesian Computation
Approximate Bayesian Computation methods (also called likelihood free inference methods), are a group of techn... | github_jupyter |
# Suave demo notebook: BAO basis on a periodic box
Hello! In this notebook we'll show you how to use suave, an implementation of the Continuous-Function Estimator, with a basis based on the standard baryon acoustic oscillation (BAO) fitting function.
```
import os
import numpy as np
import matplotlib.pyplot as plt
i... | github_jupyter |
<a href="https://colab.research.google.com/github/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_01_3_python_collections.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# T81-558: Applications of Deep Neural Networks
**Module 1: Python P... | github_jupyter |
## Compare CBC and Gurobi
Compare the computation time of the CBC and Gurobi solvers for the same scenarios
```
import logging
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rcParams['pdf.fonttype'] = 42
mpl.rcParams['ps.fonttype'] = 42
import numpy as np
import random
import seaborn as sns
import panda... | github_jupyter |
```
txt = '''Coronavirus disease 2019 (COVID-19), also known as the coronavirus, or COVID, is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019.[7] The disease has since spread worldwide, leading to an ongoi... | github_jupyter |
**Sustainable Software Development, block course, March 2021**
*Scientific Software Center, Institute for Scientific Computing, Dr. Inga Ulusoy*
# Analysis of the data
Imagine you perform a "measurement" of some type and obtain "scientific data". You know what your data represents, but you have only a vague idea ho... | github_jupyter |
# Implementing Simple Linear regression
Python implementation of the linear regression exercise from Andrew Ng's course: Machine Learning on coursera.
Exercise 1
Source notebooks:
[1][1]
[2][2]
[3][3]
[4][4]
[1]:https://github.com/kaleko/CourseraML/blob/a815ac95ba3d863b7531926b1edcdb4f5dd0eb6b/ex1/ex1.ipynb
[2... | github_jupyter |
```
import pandas as pd
import numpy as np
import calendar
import math
import re
import string
import segmentation
import utils
import data2graph
from finetuned import T5FineTuner, BARTFineTuner, generate, generate_beam, graph2text_nobeam, graph2text_nobeam_ngram_es, graph2text_nobeam_topk, graph2text_nobeam_topp
impor... | github_jupyter |
```
from IPython.display import HTML
tag = HTML('''<script>
code_show=true;
function code_toggle() {
if (code_show){
$('div.input').hide()
} else {
$('div.input').show()
}
code_show = !code_show
}
$( document ).ready(code_toggle);
</script>
Toggle cell visibility <a href="javascript:c... | github_jupyter |
# PRMS v6 BMI coupling - runtime interaction demo
* This demonstration will illustrate how the coupled surface-, soil-, groundwater-, and streamflow-BMIs can be interacted with at runtime.
* Some initial setup including matching an HRU polygon shapefile with order of HRUs in input file
* Visualizing results by... | github_jupyter |
# Ingest data with Redshift
This notebook demonstrates how to set up a database with Redshift and query data with it. We are going to use the data we load into S3 in the previous notebook [011_Ingest_tabular_data.ipynb](011_Ingest_tabular_data_v1.ipynb) and database and schema we created in [02_Ingest_data_with_Athena.... | github_jupyter |
<a href="https://colab.research.google.com/github/Manan1811/FaceNet-Model/blob/main/FaceNet_Model2.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
!nvidia-smi
from google.colab import drive
drive.mount('/content/drive')
!wget https://data.vision... | github_jupyter |
[Index](Index.ipynb) - [Back](Widget Styling.ipynb) - [Next](Widget Asynchronous.ipynb)
```
from __future__ import print_function
```
# Building a Custom Widget - Hello World
The widget framework is built on top of the Comm framework (short for communication). The Comm framework is a framework that allows the kerne... | github_jupyter |
```
%load_ext autoreload
%autoreload 2
```
> **How to run this notebook (command-line)?**
1. Install the `ReinventCommunity` environment:
`conda env create -f environment.yml`
2. Activate the environment:
`conda activate ReinventCommunity`
3. Execute `jupyter`:
`jupyter notebook`
4. Copy the link to a browser
# `REI... | github_jupyter |
<a href="https://colab.research.google.com/github/RSNA/AI-Deep-Learning-Lab-2021/blob/main/sessions/object-detection-seg/segmentation.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Overview
In this tutorial we will explore how to create a contra... | github_jupyter |
© 2020 Nokia
Licensed under the BSD 3 Clause license
SPDX-License-Identifier: BSD-3-Clause
## Setup
```
%load_ext autoreload
%autoreload 2
import os
import json
import time
import numpy as np
import sys
from codesearch.encoders import BasicEncoder
from codesearch import embedding_pretraining
from codesearch.embed... | github_jupyter |
# Word2Vec with CNN and Bi-LSTM - word2vec vector values as weights for LSTM to train
```
import numpy as np
import pandas as pd
import os
import nltk
import sklearn
from gensim.models import Word2Vec
import re
import multiprocessing
import tensorflow as tf
from keras.preprocessing.text import Tokenizer
from collectio... | github_jupyter |
```
import requests
import datetime
from datetime import datetime as dt
import patoolib
import os
import pandas as pd
import sqlalchemy
import psycopg2
from sqlalchemy import create_engine
import numpy as np
from datetime import timedelta
import os.path
from datetime import datetime
import sqlalchemy as sa
#from sqlal... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set()
from google.colab import files
uploaded = files.upload()
```
### ***Train Data***
```
train_data = pd.read_excel('Data_Train.xlsx')
pd.set_option('display.max_columns',None)
train_data.head()... | github_jupyter |
# Training Neural Networks
The network we built in the previous part isn't so smart, it doesn't know anything about our handwritten digits. Neural networks with non-linear activations work like universal function approximators. There is some function that maps your input to the output. For example, images of handwritt... | github_jupyter |
# Class Session 2
## Comparing running times for enumerating neighbors of all vertices in a graph (with different graph data structures)
In this notebook we will measure the running time for enumerating the neighbor vertices for three different data structures for representing an undirected graph:
- adjacency matrix
... | github_jupyter |
# Example: CanvasXpress scatter2d Chart No. 1
This example page demonstrates how to, using the Python package, create a chart that matches the CanvasXpress online example located at:
https://www.canvasxpress.org/examples/scatter2d-1.html
This example is generated using the reproducible JSON obtained from the above p... | github_jupyter |
##### Copyright 2018 The TensorFlow Probability Authors.
Licensed under the Apache License, Version 2.0 (the "License");
```
#@title Licensed under the Apache License, Version 2.0 (the "License"); { display-mode: "form" }
# you may not use this file except in compliance with the License.
# You may obtain a copy of th... | github_jupyter |
```
import os, sys, gc
import time
import glob
import pickle
import copy
import json
import random
from collections import OrderedDict, namedtuple
import multiprocessing
import threading
import traceback
from typing import Tuple, List
import h5py
from tqdm import tqdm, tqdm_notebook
import numpy as np
import pandas ... | github_jupyter |
# Getting Started
## Install Dependencies
This is a tutorial of using D4 in Python. Before you started trying this document, please make sure you have D4 package and `d4tools` binary installed.
* To install the d4tools binary, please read the instruction from [this link](https://github.com/38/d4-format#installation... | github_jupyter |
# Fast Fourier Transform Forecasting Model (FFT)
The following is a brief demonstration of the FFT forecasting model. This model is especially suited for data that is very seasonal. The datasets chosen for this demonstration were selected accordingly.
```
# fix python path if working locally
from utils import fix_pyth... | github_jupyter |
# Introduction
Involve 10 Models Clustering
<br>
<br>
<font color = 'blue'>
<b>Content: </b>
1. [Prepare Problems]
* [Load Libraries](#2)
* [Load Dataset](#3)
1. [Models]
* [K-Means](#4)
* [Affinity Propagation](#5)
* [BIRCH](#6)
* [DBSCAN](#7)
* [Mini Batch K-Means](#8)
* [Mean ... | github_jupyter |
# Robot Class
In this project, we'll be localizing a robot in a 2D grid world. The basis for simultaneous localization and mapping (SLAM) is to gather information from a robot's sensors and motions over time, and then use information about measurements and motion to re-construct a map of the world.
### Uncertainty
A... | github_jupyter |
```
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import numpy as np
import sklearn as sk
import seaborn as sns
import statsmodels.api as sm
import statsmodels.formula.api as smf
import statsmodels.tsa.api as smt
import itertools
import warnings
import scipy.signal as sp
import... | github_jupyter |
# An example of the Nonlinear inference with multiple latent functions.
This notebook briefly shows an example for an inverse problem where multiple latent functions to be infered.
*Keisuke Fujii 3rd Oct. 2016*
## Synthetic observation
Consider we observe a cylindrical transparent mediam with multiple ($N$) lines-o... | github_jupyter |
```
from mcts_simple import Game
class TicTacToe(Game):
def __init__(self):
self.board = {char + str(num + 1): " " for char in "abc" for num in range(3)}
self.players = ["X", "O"]
self.player_turn = 0
self.prev_actions = []
def win_conditions(self):
return ((self.board[... | github_jupyter |
```
########################################
## import packages
########################################
import os
import re
import csv
import codecs
import numpy as np
import pandas as pd
import operator
from nltk.corpus import stopwords
from nltk.stem import SnowballStemmer
from string import punctuation
from textbl... | github_jupyter |
# Effect of learning rate
In this notebook, we will discuss the impact of learning rate, which will determine step size and change the distance from initialzation to the solution, which contributes to breaking the NTK regime.
```
import torch
from torch import optim, nn
from torchvision import datasets, transforms
fr... | github_jupyter |
## Day 3: Cells in Silicon
Welcome to Day 3! Today, we start with our discussion with the Hodgkin Huxley Neurons and how we can simulate them in python using Tensorflow and Numerical Integration.
### What is the Hodgkin Huxley Neuron Model?
(Modified from Neuronal Dynamics, EPFL)
Hodgkin and Huxley performed many e... | github_jupyter |
# Styling
*New in version 0.17.1*
<span style="color: red">*Provisional: This is a new feature and still under development. We'll be adding features and possibly making breaking changes in future releases. We'd love to hear your feedback.*</span>
This document is written as a Jupyter Notebook, and can be viewed or d... | github_jupyter |
## Engineering Rare Categories
Rare values are categories within a categorical variable that are present only in a small percentage of the observations. There is no rule of thumb to determine how small is a small percentage, but typically, any value below 5 % can be considered rare.
As we discussed in section 3 of th... | github_jupyter |
# Projet Morpion
par *Hélène et Victoria* ; Bugnon Ours, oc.info 2018/2019
Morpion est un jeux simple qui se joue sur un cadrillage 3x3. Le but est d'aligner 3 jetons en colonne, ligne au en diagonale.
Le jeux est joué sur la plateforme SenseHAT pour le Raspberry Pi. Dans ce notebook, des fragment de code sont expliq... | github_jupyter |
# K-Nearest Neighbors Algorithm
* Last class, we introduced the probabilistic generative classifier.
* As discussed, the probabilistic generative classifier requires us to assume a parametric form for each class (e.g., each class is represented by a multi-variate Gaussian distribution, etc..). Because of this, the ... | github_jupyter |
### HGT features in A. castellanii
**cmdoret, 20201009**
In this notebook, I compare the nucleotide composition and general features of A.castallanii genes with HGT candidates. I previously computed the following genome composition metrics in 1kb non-overlapping sliding windows:
* GC content $\frac{G+C}{A+C+G+T}$
* GC... | github_jupyter |
# Project: Create a Convolutional Neural Network
- We will create a model on the [CIFAR-10 dataset](https://www.cs.toronto.edu/%7Ekriz/cifar.html)
### Step 1: Import libraries
```
import tensorflow as tf
from tensorflow.keras import datasets, layers, models
from tensorflow.keras.models import Sequential
from tensorfl... | github_jupyter |
# K Nearest Neighbors Classifiers
So far we've covered learning via probability (naive Bayes) and learning via errors (regression). Here we'll cover learning via similarity. This means we look for the datapoints that are most similar to the observation we are trying to predict.
#### What type of model is k-nearest ne... | github_jupyter |
# COVID-19: Healthcare Facility Capacity Optimization
## Objective and Prerequisites
This COVID-19 Healthcare Facility Capacity Optimization problem shows you how to determine the optimal location and capacity of healthcare facilities in order to:
* Satisfy demand from COVID-19 patients for treatment,
* Minimize the... | github_jupyter |
### MEDC0106: Bioinformatics in Applied Biomedical Science
<p align="center">
<img src="../../resources/static/Banner.png" alt="MEDC0106 Banner" width="90%"/>
<br>
</p>
---------------------------------------------------------------
# 11 - Introduction to Biopython - Proteins
*Written by:* Mateusz Kaczyński
**... | github_jupyter |
# Proyecto - Calculadora
## **Programación**
### *Universidad Central*
### *Elaborado por:*
* Juan Castillo (Interfaz gráfica, Cálculo Vectorial)
* Laura Contreras (Pre-Álgebra, gráficas)
* Carlos Carvajales (Cálculo diferencial)
* Jessica Santos (Álgebra lineal)
* María García (Cálculo Integral)
Querido usuario,... | github_jupyter |
<a href="https://colab.research.google.com/github/VinACE/san_mrc/blob/master/longformer_qa_training.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Longformer for Question Answering
```
!nvidia-smi
!git clone https://github.com/huggingface/transf... | github_jupyter |
# Autobatching log-densities example
This notebook demonstrates a simple Bayesian inference example where autobatching makes user code easier to write, easier to read, and less likely to include bugs.
Inspired by a notebook by @davmre.
```
from __future__ import absolute_import
from __future__ import division
from _... | github_jupyter |
# 通过PYNQ加速OPENCV函数(Sobel算子)
在阅读本部分UserGuide时,请确认已做好以下准备：
* 已经按照之前的预备文档安装好依赖环境<br>
* 2根HDMI传输线(对输入视频流以及输出视频流进行测试)
* 一台支持HDMI的显示器(对输入视频流以及输出视频流进行测试)
## 步骤1：加载cv2pynq库
```
import cv2pynq as cv2
```
在正常运行的情况下,可以看到PYNQ板卡标记为“DONE”的LED闪烁(为加载了bit文件的效果);
这是由于在封装的时候,我们在初始化阶段调用了Overlay方法给PYNQ加载了定制的bit文件:
```python
def __i... | github_jupyter |
# Logistic Regression with a Neural Network mindset
Welcome to your first (required) programming assignment! You will build a logistic regression classifier to recognize cats. This assignment will step you through how to do this with a Neural Network mindset, and so will also hone your intuitions about deep learning.... | github_jupyter |
# Image Data Storage for the Web
## Learning objectives
- Become familiar with the design of modern, **cloud storage systems**
- Gain experience with the **zarr** and **n5 formats**
- Understand the relationship between **chunked, compressed**, object storage and **parallel processing and multi-scale visualization**
... | github_jupyter |
This example shows how to create a radial profile from a SOXS event file, including using an exposure map to get flux-based quantities. We'll simulate a simple isothermal cluster.
```
import matplotlib
matplotlib.rc("font", size=18)
import matplotlib.pyplot as plt
import soxs
import astropy.io.fits as pyfits
```
Firs... | github_jupyter |
**Chapter 5 – Support Vector Machines**
_This notebook contains all the sample code and solutions to the exercises in chapter 5._
<table align="left">
<td>
<a target="_blank" href="https://colab.research.google.com/github/ageron/handson-ml/blob/master/05_support_vector_machines.ipynb"><img src="https://www.tens... | 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 |
```
# test the nn pipeline
import sys
sys.path.insert(0,"/Users/rezaie/github/DESILSS")
import NN
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from sklearn.model_selection import KFold
def split2Kfolds(data, k=5, shuffle=True, random_seed=123):
'''
split data into k randomly chosen ... | github_jupyter |
## Coming soon in `numba` 0.34
You can install the release candidate as of 07/09/2017 from the `numba` conda channel
```
conda install -c numba numba
```
```
import numpy
from numba import njit
```
Define some reasonably expensive operation in a function.
```
def do_trig(x, y):
z = numpy.sin(x**2) + numpy.cos(... | github_jupyter |
```
from __future__ import print_function
import pandas as pd
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import statsmodels.api as sm
from statsmodels.graphics.api import qqplot
%matplotlib inline
dta=[10930,10318,10595,10972,7706,6756,9092,10551,9722,10913,11151,8186,6422,
6337,11649,... | github_jupyter |
# Deming Regression
-------------------------------
This function shows how to use TensorFlow to solve linear Deming regression.
$y = Ax + b$
We will use the iris data, specifically:
y = Sepal Length and x = Petal Width.
Demming regression is also called total least squares, in which we minimize the shortest dista... | github_jupyter |
# Test of widgets
* lets see what we got here
```
# try the following:
#!pip install ipywidgets==7.4.2
#!pip install bqplot
# lets import our usual stuff
import pandas as pd
import bqplot
import numpy as np
import traitlets
import ipywidgets
%matplotlib inline
data = np.random.random((10, 10))
# now add scales - col... | github_jupyter |
TSG098 - Get BDC replicasets (Kubernetes)
=========================================
Description
-----------
Steps
-----
### Common functions
Define helper functions used in this notebook.
```
# Define `run` function for transient fault handling, suggestions on error, and scrolling updates on Windows
import sys
imp... | github_jupyter |
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