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# Chapter 4
## Question 11
Using the `Auto` data set to predict whether a given car has high or low mileage (seems like a regression on `mpg` to me?)
```
import statsmodels.api as sm
import numpy as np
import seaborn as sns
import sklearn.model_selection
import sklearn.discriminant_analysis
import sklearn.neighbors
... | github_jupyter |
# Time series forecasting with DeepAR - Synthetic data
DeepAR is a supervised learning algorithm for forecasting scalar time series. This notebook demonstrates how to prepare a dataset of time series for training DeepAR and how to use the trained model for inference.
```
import time
import numpy as np
np.random.seed(... | github_jupyter |
```
import cv2
import numpy as np
import matplotlib.pyplot as plt
import glob
import pathlib
%matplotlib inline
class ColorReduction:
def __call__(self, img):
if len(img.shape) == 3:
return self.apply_3(img)
if len(img.shape) == 2:
return self.apply_2(img)
return None... | github_jupyter |
```
import pandas as pd
import csv
import re
# names of files to read from
r_maxo_classes_with_definitionsTSV = '~/Git/MAxO/src/ontology/sparql-test/maxo_classes_with_definitions.tsv'
r_ncit_definitionsTSV = '~/Git/MAxO/src/ontology/sparql-test/ncit_definitions.tsv'
tsv_read_maxo = pd.read_csv(r_maxo_classes_with_defi... | github_jupyter |
# RNA velocity analysis using scVelo
* __Notebook version__: `v0.0.1`
* __Created by:__ `Imperial BRC Genomics Facility`
* __Maintained by:__ `Imperial BRC Genomics Facility`
* __Docker image:__ `imperialgenomicsfacility/scanpy-notebook-image:release-v0.0.4`
* __Github repository:__ [imperial-genomics-facility/scanpy-... | github_jupyter |
# Querying WikiData for henet edges
```
import json
import pandas as pd
from pathlib import Path
from datetime import datetime
from tqdm import tqdm_notebook
# ModuleNotFoundError
## edited "hetnet_ml.src" to "hetnet_ml" in .py script
import wdhetnetbuilder as wdh # make sure wikidataintegrator is installed ## pip in... | github_jupyter |
```
import pandas as pd
import seaborn as sns
import sys
from matplotlib import pyplot as plt
%matplotlib inline
MIN_PYTHON = (3, 6)
if sys.version_info < MIN_PYTHON:
sys.exit("Python %s.%s or later is required.\n" % MIN_PYTHON)
in_data = pd.read_csv('afterfix_speed_test.log.csv',
index_col='TS... | github_jupyter |
# Tema 03: Control de flujo (Enunciados)
*Nota: Estos ejercicios son optativos para hacer al final de la unidad y están pensados para apoyar tu aprendizaje*.
**1) Realiza un programa que lea dos números por teclado y permita elegir entre 3 opciones en un menú:**
* Mostrar una suma de los dos números
* Mostrar una res... | github_jupyter |
# `yacman` features and usage
This short tutorial show you the features of `yacman` package in action.
First, let's prepare some data to work with
```
import yaml
yaml_dict = {'cfg_version': 0.1, 'lvl1': {'lvl2': {'lvl3': {'entry': ['val1', 'val2']}}}}
yaml_str = """\
cfg_version: 0.1
lvl1:
lvl2:
lvl3:
e... | github_jupyter |
## SIS on Beer Reviews - Model Training Aspect 1 (Aroma)
```
import numpy as np
from matplotlib import pyplot as plt
import seaborn as sns
import os
import sys
import gzip
sys.path.insert(0, os.path.abspath('..'))
from keras.callbacks import ModelCheckpoint
from keras.models import load_model, Model, Sequential
from ... | github_jupyter |
```
"""
Update Parameters Here
"""
CONTRACT_ADDRESS = "0x9A534628B4062E123cE7Ee2222ec20B86e16Ca8F"
COLLECTION = "MekaVerse"
METHOD = "raritytools"
TOKEN_COL = "TOKEN_ID" # Use TOKEN_NAME if you prefer to infer token id from token name
NUMBERS_TO_CHECK = 50 # Number of tokens to search for opportunities
import time
im... | github_jupyter |
```
import tensorflow as tf
import os
os.environ['CUDA_VISIBLE_DEVICES'] = ''
import tensorflow as tf
import numpy as np
# !wget https://raw.githubusercontent.com/tensorflow/models/master/research/slim/nets/inception_utils.py
import tensorflow.compat.v1 as tf
import tf_slim as slim
import inception_utils
def bloc... | github_jupyter |
Find this notebook in https://colab.research.google.com/github/ricardokleinklein/NLP_GenMods/blob/main/Tacotron2.ipynb
# Modelos Generativos
## Tacotron2 - Audio
Creado por *Ricardo Kleinlein* para [Saturdays.AI](https://saturdays.ai/).
Dis... | github_jupyter |
```
####This notebook required run on parallel algorithms which base on MPI####
import numpy as np
import libpysal as ps
from stwr.gwr import GWR, MGWR,STWR
from stwr.sel_bw import *
from stwr.utils import shift_colormap, truncate_colormap
import geopandas as gp
import matplotlib.pyplot as plt
import matplotlib as ... | github_jupyter |
```
import tensorflow as tf
print(tf.__version__)
!ls ../chapter_07/train_base_model/tf_datasets/
!ls -lrt /content/tfrecord-dataset/flowers
import tensorflow as tf
import tensorflow_hub as hub
import tensorflow_datasets as tfds
import os
import matplotlib.pyplot as plt
from PIL import Image, ImageOps
import IPython.di... | github_jupyter |
```
from __future__ import division
import numpy as np
from pyspark import SparkConf
from pyspark import SparkContext
conf = SparkConf()
conf.setMaster('spark://ip-172-31-9-200:7077')
conf.setAppName('spark_analytics_chpt_4')
conf.set("spark.executor.memory", "10g")
sc = SparkContext(conf=conf)
```
Data from https://... | github_jupyter |
# Brain connectome comparison using geodesic distances
**Authors:** S. Shailja and B.S. Manjunath
**Affiliation:** University of California, Santa Barbara
The goal of this notebook is to study the importance of geodesic distances on manifolds. Towards that end, we propose the following twin study. We utilize the st... | github_jupyter |
```
import torch
import torch.nn as nn
import numpy as np
import matplotlib.pyplot as plt
import sklearn.datasets as skl
import torch.linalg as lin
```
## LQR with deterministic dynamics
위에 기술된 최적화 문제는
환경 $f(\textbf{x}_t, \textbf{u}_t)$ 가 선형(Linear)이고, Cost function이 Quadratic... | github_jupyter |
# BERT NER
[Model files available here. They are quite large](https://drive.google.com/open?id=11CPrF1rlZ-5eCv0m-UlFiAbCy3Z-yG54)
### Setting up workspace
```
import os
import pathlib
# *********************************************************
# If you actually want to train, switch to GPU runtime now.
# ***********... | github_jupyter |
```
import os
import warnings
from datetime import datetime, timedelta
from typing import Tuple
import matplotlib.pyplot as plt
import pandas as pd
from dotenv import load_dotenv
from prometheus_api_client import MetricSnapshotDataFrame, MetricRangeDataFrame, PrometheusConnect
from prometheus_api_client.utils import p... | github_jupyter |
##### Exercise 5.1
Consider the diagrams on the right in Figure 5.2. Why does the value function jump up for the last two rows in the rear? Why does it drop off for the whole last row on the left? Why are the frontmost values higher in the upper diagrams than in the lower?
Jumps up for last two rows in the rear sinc... | github_jupyter |
```
%load_ext autoreload
import numpy as np
import os
import matplotlib.pyplot as plt
import pickle
from enterprise import constants as const
from enterprise.signals import parameter
from enterprise.signals import selections
from enterprise.signals import signal_base
from enterprise.signals import white_signals
from e... | github_jupyter |
<a href="https://colab.research.google.com/github/unicamp-dl/IA025_2022S1/blob/main/ex02/Fernanda_Caldas/FernandaCaldas_Semana2.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Notebook de referência
Nome: Fernanda Caldas
## Instruções
Este exe... | github_jupyter |
# Subscriber with JSON export
__NOTE__: this is an __outdated__ notebook, some of the functions that are used here are considered __private__ to QCoDeS and are not intended for use by users (for example, `DataSet.subscribe`). This notebook will be re-written in the future.
```
import logging
import copy
import numpy ... | github_jupyter |
##### Copyright 2020 The Cirq Developers
```
#@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 agre... | github_jupyter |
# Analysis Report
We report the following SageMaker analysis.
## Pre-training Bias Metrics
We computed the bias metrics for the label `sentiment` using label value(s)/threshold `1`.
* **product_category**
The groups are represented in the dataset with the following proportions.
<img src='data:image/p... | github_jupyter |
## Campaign 2, Day 1
***
#### STEP 1 (day1_step1_TransferCells.hso)
* Transfer 180uL cells from 12 channel reservoir - column 1 to BlackwClearBottomAssay - columns 1-6
* Transfer 180uL cells from 12 channel reservoir - column 1 to BlackwClearBottomAssay - columns 7-12
#### STEP 2 (day1_step2_DiluteMuconate... | github_jupyter |
```
import json
import re
import sentencepiece as spm
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '1'
from prepro_utils import preprocess_text, encode_ids, encode_pieces
sp_model = spm.SentencePieceProcessor()
sp_model.Load('sp10m.cased.bert.model')
with open('sp10m.cased.bert.vocab') as fopen:
v = fopen.read(... | github_jupyter |
# Visually Shaping Distributions with TrafPy
This Notebook shows an example of how to shape distributions with `TrafPy`. We will save our shaped distributions, re-load them, and use them to generate custom flow-centric traffic data, which we will then save in .pickle format such that you'd be able to import the traffi... | github_jupyter |
```
import os
from concurrent.futures import ProcessPoolExecutor
from pathlib import Path
import matplotlib.pyplot as plt
from lhotse import CutSet, Fbank, LilcomFilesWriter
from lhotse.augmentation import SoxEffectTransform, RandomValue
from lhotse.dataset import K2SpeechRecognitionDataset
from lhotse.dataset.sampli... | github_jupyter |
reference: [Google Colab Python API](https://worldbank.github.io/OpenNightLights/tutorials/mod2_5_GEE_PythonAPI_and_geemap.html#google-colab-python-api)
```
import geemap, ee
```
`True` if run in Colab; `False` if local
```
'google.colab' in str(get_ipython())
try:
ee.Initialize()
except Exception as e:
... | github_jupyter |
### Working with Avro files
Here are some examples of working with ZTF alerts stored as avro files.
```
import os
import io
import gzip
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from avro.datafile import DataFileReader, DataFileWriter
from avro.io import DatumReader, DatumWriter
import f... | github_jupyter |
```
%matplotlib inline
import numpy as np
import pylab as plt
import cv2
data_root = '/diskmnt/a/makov/yaivan/2016-02-11_Pin/'
```
Список файлов:
* empty - файл полученный с томографа без коррекций
* corr - то же изображение что и empty, но с коррекцией
* tomo - то же, что и empty, но полученное в ходе проведения эксп... | github_jupyter |
```
%load_ext autoreload
%autoreload 2
import ray
import ray.rllib.agents.ppo as ppo
from ray.tune.logger import pretty_print
from ray import tune
from ray.rllib.agents.ppo import PPOTrainer
from ray.rllib.models import FullyConnectedNetwork, Model, ModelCatalog
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] =... | github_jupyter |
```
# !pip install kfp
# !pip install google-cloud-aiplatform
# !pip install google-cloud-pipeline-components
import kfp
from kfp.v2 import compiler
from kfp.v2.google.client import AIPlatformClient
from google.cloud import aiplatform
# from google.cloud.aiplatform import pipeline_jobs
from google_cloud_pipeline_compon... | github_jupyter |
# 1.Loading libraries and Dataset
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
import warnings
warnings.filterwarnings('ignore')
from sklearn.model_selection import KFold
from sklearn.model_selection import train_test_split
from sklearn.model_sel... | github_jupyter |
<img align="center" style="max-width: 1000px" src="banner.png">
<img align="right" style="max-width: 200px; height: auto" src="hsg_logo.png">
## Lab 03 - "Supervised Machine Learning" Assignments
GSERM'21 course "Deep Learning: Fundamentals and Applications", University of St. Gallen
The lab environment of the "De... | github_jupyter |
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT License.
# AML P... | github_jupyter |
## WaMDaM Directions and Use Cases
#### By Adel M. Abdallah, Utah State University, August 2018
The Water Management Data Model (WaMDaM) is a database design with companion software that uses contextual metadata and controlled vocabularies to organize water management data from multiple sources and models. The des... | github_jupyter |
```
import cv2
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
class Interpolation:
def bilinear(self, img, scale=1.5):
H, W = img.shape[:2]
H_big, W_big = int(H * scale), int(W * scale)
if len(img.shape) == 2:
ch = 1
output_img = np.zeros((H_big... | github_jupyter |
# Stablecoin Billionaires<br> Descriptive Analysis of the Ethereum-based Stablecoin ecosystem
## by Anton Wahrstätter, 01.07.2020
# Part II - USDC
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
from collections import Counter
from matplotlib import rc
import ... | github_jupyter |
# Data collection
In this notebook, I'll use the **GitHub API** to extract various information from my user profile such as repositories, commits and more. I'll also save this data to **.csv** files so that I can draw insights.
## Import libraries and defining constants
I'll import various libraries needed for fetch... | github_jupyter |
# Bigram
https://towardsdatascience.com/text-analysis-basics-in-python-443282942ec5
# Loading data
```
import pandas as pd
import numpy as np
#agar mudah, letakkan file data dalam satu folder dengan file jupiter notebook nya
filedata = 'discussion'
dataSB = pd.read_excel(filedata+".xlsx", sheet_name="Sheet1")
da... | github_jupyter |
# Chapter 8: Planning and Learning with Tabular Methods
## 1. Models and Planning
- **model-based** methods:
- require a model of enviroment (DP, HS)
- rely on **planning**
- **model-free** methods:
- does not require a model of enviroment (MC, TD)
- rely on **learning**
- heart of 2 methods is the com... | github_jupyter |
**This notebook is an exercise in the [Intermediate Machine Learning](https://www.kaggle.com/learn/intermediate-machine-learning) course. You can reference the tutorial at [this link](https://www.kaggle.com/alexisbcook/data-leakage).**
---
Most people find target leakage very tricky until they've thought about it fo... | github_jupyter |
# Bagging Double Deep Q Learning - A simple ambulance dispatch point allocation model
## Reinforcement learning introduction
### RL involves:
* Trial and error search
* Receiving and maximising reward (often delayed)
* Linking state -> action -> reward
* Must be able to sense something of their environment
* Involves... | github_jupyter |
https://github.com/VowpalWabbit/vowpal_wabbit
webspam: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html
Реализация стохастического градиентного спуска для линейхных моделей, позволяющая запускаться на больших объёмах данных, за счет последовательной загрузки и обработки примеров.
... | github_jupyter |
```
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasRegressor
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import KFold
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline
from keras.op... | github_jupyter |
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT License.
# ... | github_jupyter |
```
#
# This MaterialsAutomated example shows how to overlay simulated Laue spots on
# experimental data in an automated fashion.
#
# It utilizes an existing open-source Laue diffraction analysis toolkit, LaueTools:
# https://gitlab.esrf.fr/micha/lauetools
#
# If the goal is to analyze a single or small number of d... | github_jupyter |
# Python Comments
Comments are lines that exist in computer programs that are ignored by compilers and interpreters.
Including comments in programs makes code more readable for humans as it provides some information or explanation about what each part of a program is doing.
In general, it is a good idea to write co... | github_jupyter |
```
import pickle
from misc import *
import SYCLOP_env as syc
from RL_brain_b import DeepQNetwork
import matplotlib.pyplot as plt
%matplotlib notebook
import cv2
from scipy import misc
import glob
datapath='/home/bnapp/arivkindNet/video_datasets/dataset-corridor1_512_16/mav0/cam0/data/'
images=[]
max_image = 2
image_cn... | github_jupyter |
# 基于注意力的神经机器翻译
此笔记本训练一个将缅甸语翻译为英语的序列到序列（sequence to sequence，简写为 seq2seq）模型。此例子难度较高，需要对序列到序列模型的知识有一定了解。
训练完此笔记本中的模型后，你将能够输入一个缅甸语句子，例如 *"ဘာကိစ္စ မဖြစ်ရ မှာ လဲ?"*，并返回其英语翻译 *"Why not?"*
对于一个简单的例子来说，翻译质量令人满意。但是更有趣的可能是生成的注意力图：它显示在翻译过程中，输入句子的哪些部分受到了模型的注意。
<img src="https://tensorflow.google.cn/images/spanish-english.png" ... | 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 _init_paths
import argparse
import os
import sys
import logging
import pprint
import cv2
from config.config import config, update_config
from utils.image import resize, transform
import numpy as np
# get config
os.environ['PYTHONUNBUFFERED'] = '1'
os.environ['MXNET_CUDNN_AUTOTUNE_DEFAULT'] = '0'
os.environ[... | github_jupyter |
# Python review of concepts
Mainly to point out useful aspects of Python you may have glossed over. Assumes you already know Python fairly well.
## Python as a language
### Why Python?
- Huge community - especially in data science and ML
- Easy to learn
- Batteries included
- Extensive 3rd party libraries
- Wi... | github_jupyter |
# MAT281
## Aplicaciones de la Matemática en la Ingeniería
## ¿Qué contenido aprenderemos?
* Manipulación de datos con ```pandas```.
- Crear objetos (Series, DataFrames, Index).
- Análisis exploratorio.
- Realizar operaciones y filtros.
- Aplicar funciones y métodos.
## Motivación
En los últimos año... | github_jupyter |
# Open and run analysis on multiple polygons <img align="right" src="../Supplementary_data/dea_logo.jpg">
* [**Sign up to the DEA Sandbox**](https://docs.dea.ga.gov.au/setup/sandbox.html) to run this notebook interactively from a browser
* **Compatibility:** Notebook currently compatible with both the `NCI` and `DEA S... | github_jupyter |
# Aula 01 - Introdução à Ciência de Dados
## Indústria 4.0 / Sociedade 5.0
<!-- Figura -->
<center>
<img src='../figs/01/society-5-industry-4.png' width=900px> </img>
</center>
[Fonte](https://www.sphinx-it.eu/from-the-agenda-of-the-world-economic-forum-2019-society-5-0/)
## Ciência de Dados no Século XXI
- D... | github_jupyter |
# CPT example: planning dual-Doppler campaign
### Nikola Vasiljevic, August 24th 2019
In this example we will use [CPT](https://www.wind-energ-sci-discuss.net/wes-2019-13/) to plan a fictive measurement campaign for a site consisting of 12x80m turbines.
<br>The site is located at the sea coast of Croatia in vicinity o... | github_jupyter |
# Unlocking the Black Box: How to Visualize Data Science Project Pipeline with Yellowbrick Library
No matter whether you are a novice data scientist or a well-seasoned and established professional working in the field for a long time, you most likely faced a challenge of interpreting results generated at any stage of ... | github_jupyter |
### Utilitary Functions
Definition of functions that don't belong to a specific class inside the logic of the problem solution
```
import numpy as np
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import math
import copy
%matplotlib inline
def pseudo_transpose(listt):
'''
Utilitary ... | github_jupyter |
# Ray RLlib - Extra Application Example - FrozenLake-v0
© 2019-2021, Anyscale. All Rights Reserved
This example uses [RLlib](https://ray.readthedocs.io/en/latest/rllib.html) to train a policy with the `FrozenLake-v0` environment ([gym.openai.com/envs/Froze... | github_jupyter |
# Artificial Intelligence in Finance
## Data-Driven Finance (a)
## Financial Econometrics and Regression
```
import numpy as np
def f(x):
return 2 + 1 / 2 * x
x = np.arange(-4, 5)
x
y = f(x)
y
x
y
beta = np.cov(x, y, ddof=0)[0, 1] / x.var()
beta
alpha = y.mean() - beta * x.mean()
alpha
y_ = alpha + beta * x
np.a... | github_jupyter |
```
# Configuracion para recargar módulos y librerías
%reload_ext autoreload
%autoreload 2
```
# MAT281
## Aplicaciones de la Matemática en la Ingeniería
Puedes ejecutar este jupyter notebook de manera interactiva:
[](https://mybinder.org/v2/gh/sebastiandres/mat281_m01... | github_jupyter |
# The Hill-Tononi Neuron and Synapse Models
## Hans Ekkehard Plesser, NMBU/FZ Jülich/U Oslo, 2016-12-01
## Background
This notebook describes the neuron and synapse model proposed by Hill and Tononi in *J Neurophysiol* 93:1671-1698, 2005 ([doi:10.1152/jn.00915.2004](http://dx.doi.org/doi:10.1152/jn.00915.2004)) and ... | github_jupyter |
```
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit.Chem import Descriptors
from sklearn.model_selection import train_test_split
from sklearn.neural_network import MLPClassifier
from sklearn.preprocessing import StandardScaler
from ... | github_jupyter |
```
import numpy as np
import matplotlib.pyplot as plt
import scipy
from sklearn.model_selection import ParameterGrid
from sklearn.manifold import Isomap
import time
from tqdm import tqdm
import librosa
from librosa import cqt
from librosa.core import amplitude_to_db
from librosa.display import specshow
import os
im... | github_jupyter |
```
import pandas as pd
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime, timedelta
from sklearn.cluster import KMeans
from sklearn.ensemble import RandomForestClassifier
import shap
```
# Loading clean data
```
import os
clean_files = ['cleaned_data/all_dataset/... | github_jupyter |
Autor: Érick Barbosa de Souza
Home: https://abre.ai/ebsouza-pagina
Instagram: @erickbsouza
---
**Programação Orientada a Objetos**
Após aprender lógica de programação utilizando **programação estruturada**, é necessário aprender novos conceitos para resolver problemas comuns em computação. A **programação orient... | github_jupyter |
<center>
<img src="https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/IDSNlogo.png" width="300" alt="cognitiveclass.ai logo" />
</center>
# Watson Speech to Text Translator
Estimated time needed: **25** minutes
## Objectives
After completing this... | github_jupyter |
```
name = '2017-06-02-matplotlib-contourf-subplots'
title = 'Filled contour plots and colormap normalization'
tags = 'matplotlib'
author = 'Maria Zamyatina'
from nb_tools import connect_notebook_to_post
from IPython.core.display import HTML, Image
html = connect_notebook_to_post(name, title, tags, author)
```
Today ... | github_jupyter |
# Symbulate Documentation
# Random Processes
<a id='contents'></a>
1. [**RandomProcess and TimeIndex**](#time)
1. [**Defining a RandomProcess explicitly as a function of time**](#Xt)
1. [**Process values at particular time points**](#value)
1. [**Mean function**](#mean)
1. [**Defining a RandomProcess increm... | github_jupyter |
# Mosaic
```
%matplotlib inline
import matplotlib.pyplot as plt
from matplotlib import rc
import matplotlib.font_manager
rc('font',**{'family':'serif','serif':['Computer Modern Roman'],'size':13})
rc('text', usetex=True)
import pandas as pd
import numpy as np
from statistics import load
def plot(ax, frame, cell_type... | github_jupyter |
# Autoencoders
## Imports
```
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.metrics import accuracy_score, precision_score, recall_score
from sklearn.model_selection import train_test_split
from tensorflow.keras import layers, losses
from tensorflow.keras... | github_jupyter |
# Homework and bake-off: Sentiment analysis
```
__author__ = "Christopher Potts"
__version__ = "CS224u, Stanford, Spring 2021"
```
## Contents
1. [Overview](#Overview)
1. [Methodological note](#Methodological-note)
1. [Set-up](#Set-up)
1. [Train set](#Train-set)
1. [Dev sets](#Dev-sets)
1. [A softmax baseline](#A-so... | github_jupyter |
# Semantic Vector Space
Construct a basic semantic vector set for disambiguating coordinate relations.
```
import collections
from datetime import datetime
from tools.langtools import PositionsTF
from tools.significance import apply_fishers, contingency_table
from tools.locations import data_locations
from cxbuilders... | github_jupyter |
# TensorFlow实现VGG16
## 导入需要使用的库
```
import inspect
import os
import numpy as np
import tensorflow as tf
```
## 定义卷积层
```
'''Convolution op wrapper, use RELU activation after convolution
Args:
layer_name: e.g. conv1, pool1...
x: input tensor, [batch_size, height, width, channels]
out_cha... | github_jupyter |
```
# conda/pip install pycircstat
import sys
import os
import math
import random
import pickle
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from scipy import stats,io
import pycircstat
from scipy.ndimage import gaussian_filter1d
```
# Functions
```
sys.path.append('... | github_jupyter |
```
# default_exp convert
```
# The Converter
> The internals for the lib2nbdev functionality
```
#hide
from nbdev.showdoc import *
#hide
from fastcore.test import *
#export
import json
from fastcore.basics import Path
from fastcore.xtras import is_listy
from fastcore.foundation import Config
from fastcore.script i... | github_jupyter |
# Working with Landsat Thematic Mapper Imagery
# Questions
- How does land change manifest itself in time-series of multispectral imagery?
- Can you identify when a significant disturbance occurred?
# Let's explore Landsat... | github_jupyter |
# Tutorial 3.1. Structural response under windload
### Description: For the given geometry, compute the shear force and the bending moment of the structure along the height for the given wind load. Compare the base shear and the bending moment at the base with other buildings of similar height
Project: Structural Wi... | github_jupyter |
# Road Following - Data Collection (using Gamepad)
If you've run through the collision avoidance sample, your should be familiar following three steps
1. Data collection
2. Training
3. Deployment
In this notebook, we'll do the same exact thing! Except, instead of classification, you'll learn a different fundamen... | github_jupyter |
## Rock, Paper & Scissors with TensorFlow Hub - TFLite
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https://colab.research.google.com/github/mohan-mj/tflite-rock_paper_scissors/blob/main/tflite_rock_paper_scissors.ipynb">
<img src="https://www.tensorflow.org/images/colab_lo... | github_jupyter |
## Preamble
```
import json
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
plt.style.use('ggplot')
import qsharp
qsharp.packages.add("Microsoft.Quantum.MachineLearning::0.14.2011120240")
qsharp.reload()
from Microsoft.Quantum.Samples import (
Tr... | github_jupyter |
# Z-score (Solution)
## Install packages
```
import sys
!{sys.executable} -m pip install -r requirements.txt
import cvxpy as cvx
import numpy as np
import pandas as pd
import time
import os
import quiz_helper
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('ggplot')
plt.rcParams['figure.figsize'] = (... | github_jupyter |
<a href="https://colab.research.google.com/github/suredream/CNN-Sentinel/blob/master/mnist.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Version Control
```
%%bash
function auth(){
echo $(grep $1 ~/.auth_git | cut -d'"' -f 4 )
}
user=$(auth... | github_jupyter |
# diverse development using pennlinckit
```
import sys
factor = sys.argv[1]
```
#### pennlinckit contains data, plotting, brain, network science, and math functions common to neuroscience projects
```
import pennlinckit
```
#### standard libraries
```
import numpy as np
import scipy.stats
import seaborn as sns
imp... | github_jupyter |
```
import pandas as pd
import numpy as np
import tensorflow as tf
from keras.models import Sequential
from keras.layers import Dense, Embedding, LSTM, SpatialDropout1D, Bidirectional
from sklearn.model_selection import train_test_split
from keras.utils.np_utils import to_categorical
from keras.callbacks import EarlySt... | github_jupyter |
# How to use ID Resolver Feature in BTE
## Important relevant modules
```
from biothings_explorer.resolve_ids import syncQuery as query
import nest_asyncio
nest_asyncio.apply()
```
## Generate some sample inputs and convert to curie format
```
ncbigenes = ["85456", "85461", "85462", "8578", "8622", "8630", "8669", ... | github_jupyter |
# Time Series Filters
```
%matplotlib inline
from __future__ import print_function
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
dta = sm.datasets.macrodata.load_pandas().data
index = pd.Index(sm.tsa.datetools.dates_from_range('1959Q1', '2009Q3'))
print(index)
dta.index = index
del... | github_jupyter |
# NumPy Data Access Using ArcPy
```
import arcpy as ARCPY
import arcpy.da as DA
inputFC = r'../data/CA_Polygons.shp'
fieldNames = ['PCR2000', 'POP2000', 'PERCNOHS']
tab = DA.TableToNumPyArray(inputFC, fieldNames)
print(tab)
```
# SSDataObject
1. Environment Settings (Except Extent)
2. Bad Records
3. Error/Warning Mes... | github_jupyter |
# Examples of all decoders (except Kalman Filter)
In this example notebook, we:
1. Import the necessary packages
2. Load a data file (spike trains and outputs we are predicting)
3. Preprocess the data for use in all decoders
4. Run all decoders and print the goodness of fit
5. Plot example decoded outputs
See "Exampl... | github_jupyter |
```
results = {'nist_mdipfl50_mymodel-hardest_trainacc': [100.0, 97.1, 93.9, 89.9, 87.8, 85.7, 85.0, 83.2, 82.1, 81.0], 'nist_mdipfl50_mymodel-hardest_valacc': [100.0, 96.2, 93.2, 88.3, 87.1, 82.9, 79.9, 81.1, 79.5, 75.1], 'nist_mdipfl50_mymodel_trainacc': [100.0, 95.1, 89.1, 87.6, 84.9, 83.3, 80.0, 76.7, 75.9, 71.2], ... | github_jupyter |
# Slider bar decline curve in python
Created by Thomas Martin, PhD canidate at [CoRE](https://core.mines.edu/) at Colorado School of Mines. Personal website is [here](https://tmartin.carrd.co/), and email is thomasmartin@mines.edu.
```
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import pyla... | github_jupyter |
Tutorial: VIC 5 Image Driver Parameter Conversion
====
***Converting parameters from ASCII VIC 4 format to netCDF VIC 5 Image Driver Format***
This Jupyter Notebook outlines one approach to converting VIC parameters from ASCII to netCDF format. For this tutorial, we'll convert three datasets from ASCII to netCDF:
1. ... | github_jupyter |
### Predict lung masks and Covid vs non-Covid classification for new patient CXR using Module 1 trained on the V7 lung segmentation database, and Module 2 trained on the HFHS dataset
```
# In[1]:
import os, sys, shutil
from os import listdir
from os.path import isfile, join
import random
import numpy as np
import cv2... | github_jupyter |
```
#import libraries
import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats
import collections
```
source: http://snap.stanford.edu/data/twitch-social-networks.html
3 réseaux de Twitch de pays différents.
```
#Read datasets
#
#GB
infile='data/musae_ENGB_edges.csv'
GB=nx.read_edg... | github_jupyter |
```
import json
import os
import geopandas as gpd
import matplotlib.pyplot as plt
import pandas as pd
import osmnx as ox
import random
import numpy as np
%matplotlib inline
cities = ['adelaide',
'auckland',
'baltimore',
'bangkok',
'barcelona',
'belfast',
'bern',
'chennai',
'mexico_city',
'cologne',
'ghent',
'graz',
'h... | github_jupyter |
# Algoritmos de Ordenação
```
from IPython.display import Image
Image("complexity.png")
```
## 1. Selection Sort
```
# Implementação
class SelectionSort(object):
def sort(self, data):
for i in range(0, len(data)-1):
min_index = self.min_index(i + 1, data)
... | github_jupyter |
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