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# 09 Strain Gage
This is one of the most commonly used sensor. It is used in many transducers. Its fundamental operating principle is fairly easy to understand and it will be the purpose of this lecture.
A strain gage is essentially a thin wire that is wrapped on film of plastic.
<img src="img/StrainGage.png" wi... | github_jupyter |
```
#export
from fastai.basics import *
from fastai.tabular.core import *
from fastai.tabular.model import *
from fastai.tabular.data import *
#hide
from nbdev.showdoc import *
#default_exp tabular.learner
```
# Tabular learner
> The function to immediately get a `Learner` ready to train for tabular data
The main fu... | github_jupyter |
# Aerospike Connect for Spark - SparkML Prediction Model Tutorial
## Tested with Java 8, Spark 3.0.0, Python 3.7, and Aerospike Spark Connector 3.0.0
## Summary
Build a linear regression model to predict birth weight using Aerospike Database and Spark.
Here are the features used:
- gestation weeks
- mother’s age
- fat... | github_jupyter |
## Concurrency with asyncio
### Thread vs. coroutine
```
# spinner_thread.py
import threading
import itertools
import time
import sys
class Signal:
go = True
def spin(msg, signal):
write, flush = sys.stdout.write, sys.stdout.flush
for char in itertools.cycle('|/-\\'):
status = char + ' ' + msg
... | github_jupyter |
## Problem 1
---
#### The solution should try to use all the python constructs
- Conditionals and Loops
- Functions
- Classes
#### and datastructures as possible
- List
- Tuple
- Dictionary
- Set
### Problem
---
Moist has a hobby -- collecting figure skating trading cards. His card collection has been growing, an... | github_jupyter |
<a href="http://cocl.us/pytorch_link_top">
<img src="https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/DL0110EN/notebook_images%20/Pytochtop.png" width="750" alt="IBM Product " />
</a>
<img src="https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/DL0110EN... | github_jupyter |
```
import nltk
from nltk.stem import PorterStemmer
from nltk.corpus import stopwords
import re
paragraph = """I have three visions for India. In 3000 years of our history, people from all over
the world have come and invaded us, captured our lands, conquered our minds.
From Alexander on... | github_jupyter |
# Classification on Iris dataset with sklearn and DJL
In this notebook, you will try to use a pre-trained sklearn model to run on DJL for a general classification task. The model was trained with [Iris flower dataset](https://en.wikipedia.org/wiki/Iris_flower_data_set).
## Background
### Iris Dataset
The dataset c... | github_jupyter |
<table class="ee-notebook-buttons" align="left">
<td><a target="_blank" href="https://github.com/giswqs/earthengine-py-notebooks/tree/master/Algorithms/landsat_radiance.ipynb"><img width=32px src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" /> View source on GitHub</a></td>
<td><a target="_blank" ... | github_jupyter |
# Import Libraries
```
from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import torchvision
from torchvision import datasets, transforms
%matplotlib inline
import matplotlib.pyplot as plt
```
## Data Transformations
We first start wi... | github_jupyter |
```
%cd /Users/Kunal/Projects/TCH_CardiacSignals_F20/
from numpy.random import seed
seed(1)
import numpy as np
import os
import matplotlib.pyplot as plt
import tensorflow
tensorflow.random.set_seed(2)
from tensorflow import keras
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.keras.regularizers im... | github_jupyter |
# basic operation on image
```
import cv2
import numpy as np
impath = r"D:/Study/example_ml/computer_vision_example/cv_exercise/opencv-master/samples/data/messi5.jpg"
img = cv2.imread(impath)
print(img.shape)
print(img.size)
print(img.dtype)
b,g,r = cv2.split(img)
img = cv2.merge((b,g,r))
cv2.imshow("image",img)
cv2.... | github_jupyter |
Create a list of valid Hindi literals
```
a = list(set(list("ऀँंःऄअआइईउऊऋऌऍऎएऐऑऒओऔकखगघङचछजझञटठडढणतथदधनऩपफबभमयरऱलळऴवशषसहऺऻ़ऽािीुूृॄॅॆेैॉॊोौ्ॎॏॐ॒॑॓॔ॕॖॗक़ख़ग़ज़ड़ढ़फ़य़ॠॡॢॣ।॥॰ॱॲॳॴॵॶॷॸॹॺॻॼॽॾॿ-")))
len(genderListCleared),len(set(genderListCleared))
genderListCleared = list(set(genderListCleared))
mCount = 0
fCount = 0
nCount = 0
f... | github_jupyter |
```
import pandas as pd
import numpy as np
import matplotlib
import seaborn as sns
import matplotlib.pyplot as plt
pd.set_option('display.max_colwidth', -1)
default = pd.read_csv('./results/results_default.csv')
new = pd.read_csv('./results/results_new.csv')
selected_cols = ['model','hyper','metric','value']
default = ... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import style
import matplotlib.ticker as ticker
import seaborn as sns
from sklearn.datasets import load_boston
from sklearn.ensemble import RandomForestClassifier, VotingClassifier, GradientBoostingClassifier
from sklearn.metrics... | github_jupyter |
# Delfin
### Installation
Run the following cell to install osiris-sdk.
```
!pip install osiris-sdk --upgrade
```
### Access to dataset
There are two ways to get access to a dataset
1. Service Principle
2. Access Token
#### Config file with Service Principle
If done with **Service Principle** it is adviced to add ... | github_jupyter |
<a href="https://colab.research.google.com/github/PradyumnaKrishna/Colab-Hacks/blob/RDP-v2/Colab%20RDP/Colab%20RDP.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# **Colab RDP** : Remote Desktop to Colab Instance
Used Google Remote Desktop & Ngrok... | github_jupyter |
```
from xml.dom import expatbuilder
import numpy as np
import matplotlib.pyplot as plt
import struct
import os
# should be in the same directory as corresponding xml and csv
eis_filename = '/example/path/to/eis_image_file.dat'
image_fn, image_ext = os.path.splitext(eis_filename)
eis_xml_filename = image_fn + ".xml"
``... | github_jupyter |
# Cryptocurrency Clusters
```
%matplotlib inline
#import dependencies
from pathlib import Path
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA
from sklearn.cluster import KMea... | github_jupyter |
Our best model - Catboost with learning rate of 0.7 and 180 iterations. Was trained on 10 files of the data with similar distribution of the feature user_target_recs (among the number of rows of each feature value). We received an auc of 0.845 on the kaggle leaderboard
#Mount Drive
```
from google.colab import drive
... | github_jupyter |
# Random Search Algorithms
### Importing Necessary Libraries
```
import six
import sys
sys.modules['sklearn.externals.six'] = six
import mlrose
import numpy as np
import pandas as pd
import seaborn as sns
import mlrose_hiive
import matplotlib.pyplot as plt
np.random.seed(44)
sns.set_style("darkgrid")
```
### Definin... | github_jupyter |
```
%matplotlib inline
```
Performance Tuning Guide
*************************
**Author**: `Szymon Migacz <https://github.com/szmigacz>`_
Performance Tuning Guide is a set of optimizations and best practices which can
accelerate training and inference of deep learning models in PyTorch. Presented
techniques often can... | github_jupyter |
# 78. Subsets
__Difficulty__: Medium
[Link](https://leetcode.com/problems/subsets/)
Given an integer array `nums` of unique elements, return all possible subsets (the power set).
The solution set must not contain duplicate subsets. Return the solution in any order.
__Example 1__:
Input: `nums = [1,2,3]`
Output: `[... | github_jupyter |
```
#r "nuget:Microsoft.ML,1.4.0"
#r "nuget:Microsoft.ML.AutoML,0.16.0"
#r "nuget:Microsoft.Data.Analysis,0.1.0"
using Microsoft.Data.Analysis;
using XPlot.Plotly;
using Microsoft.AspNetCore.Html;
Formatter<DataFrame>.Register((df, writer) =>
{
var headers = new List<IHtmlContent>();
headers.Add(th(i("index")))... | github_jupyter |
# Chapter 8 - Applying Machine Learning To Sentiment Analysis
### Overview
- [Obtaining the IMDb movie review dataset](#Obtaining-the-IMDb-movie-review-dataset)
- [Introducing the bag-of-words model](#Introducing-the-bag-of-words-model)
- [Transforming words into feature vectors](#Transforming-words-into-feature-ve... | github_jupyter |
<a href="https://colab.research.google.com/github/satyajitghana/TSAI-DeepNLP-END2.0/blob/main/09_NLP_Evaluation/ClassificationEvaluation.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
! pip3 install git+https://github.com/extensive-nlp/ttc_nlp ... | github_jupyter |
# MultiGroupDirectLiNGAM
## Import and settings
In this example, we need to import `numpy`, `pandas`, and `graphviz` in addition to `lingam`.
```
import numpy as np
import pandas as pd
import graphviz
import lingam
from lingam.utils import print_causal_directions, print_dagc, make_dot
print([np.__version__, pd.__ver... | github_jupyter |
Pandas est le package de prédilection pour traiter des données structurées.
Pandas est basé sur 2 structures extrêmement liées les Series et le DataFrame.
Ces deux structures permettent de traiter des données sous forme de tableaux indexés.
Les classes de Pandas utilisent des classes d... | github_jupyter |
```
#@title Copyright 2020 Google LLC. Double-click here for license information.
# 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 requ... | github_jupyter |
## Analisis de O3 y SO2 arduair vs estacion universidad pontificia bolivariana
Se compararon los resultados generados por el equipo arduair y la estacion de calidad de aire propiedad de la universidad pontificia bolivariana seccional bucaramanga
Cabe resaltar que durante la ejecucion de las pruebas, el se sospechaba e... | github_jupyter |
## Accessing TerraClimate data with the Planetary Computer STAC API
[TerraClimate](http://www.climatologylab.org/terraclimate.html) is a dataset of monthly climate and climatic water balance for global terrestrial surfaces from 1958-2019. These data provide important inputs for ecological and hydrological studies at g... | github_jupyter |
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT License.
# Automated Machine Learning
_**ディープラーンニングを利用したテキスト分類**_
## Contents
1. [事前準備](#1.-事前準備)
1. [自動機械学習 Automated Machine Learning](2.-自動機械学習-Automated-Machine-Learning)
1. [結果の確認](#3.-結果の確認)
## 1. 事前準備
本デモンストレーションでは、AutoML の深層学習... | github_jupyter |
<a href="https://colab.research.google.com/github/pszemraj/ml4hc-s22-project01/blob/autogluon-results/notebooks/colab/automl-baseline/process_autogluon_results.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
#process_autogluon_results
- cleans up t... | github_jupyter |
<h1> Repeatable splitting </h1>
In this notebook, we will explore the impact of different ways of creating machine learning datasets.
<p>
Repeatability is important in machine learning. If you do the same thing now and 5 minutes from now and get different answers, then it makes experimentation is difficult. In other... | github_jupyter |
Import the necessary imports
```
from __future__ import print_function, division, absolute_import
import tensorflow as tf
from tensorflow.contrib import keras
import numpy as np
import os
from sklearn import preprocessing
from sklearn.metrics import confusion_matrix
import itertools
import cPickle #python 2.x
#impor... | github_jupyter |
# IDS Instruction: Regression
(Lisa Mannel)
## Simple linear regression
First we import the packages necessary fo this instruction:
```
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error, mean_absolut... | github_jupyter |
```
import numpy as np
import pandas as pd
from datetime import date
from random import seed
from random import random
import time
import scipy, scipy.signal
import os, os.path
import shutil
import matplotlib
import matplotlib.pyplot as plt
from pylab import imshow
# vgg16 model used for transfer learning on the dog... | github_jupyter |
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cross_validation import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.preprocessing import StandardScaler
data = pd.read_csv('Social_Network_Ads.csv')
data.head()
data.isnull().sum()
from sklearn import ... | github_jupyter |
# Spark SQL
Spark SQL is arguably one of the most important and powerful features in Spark. In a nutshell, with Spark SQL you can run SQL queries against views or tables organized into databases. You also can use system functions or define user functions and analyze query plans in order to optimize their workloads. Th... | github_jupyter |
```
import numpy as np
import cv2
import matplotlib
import matplotlib.pyplot as plt
import matplotlib as mpimg
import numpy as np
from IPython.display import HTML
import os, sys
import glob
import moviepy
from moviepy.editor import VideoFileClip
from moviepy.editor import *
from IPython import display
from IPython.cor... | github_jupyter |
## Как выложить бота на HEROKU
*Подготовил Ян Пиле*
Сразу оговоримся, что мы на heroku выкладываем
**echo-Бота в телеграме, написанного с помощью библиотеки [pyTelegramBotAPI](https://github.com/eternnoir/pyTelegramBotAPI)**.
А взаимодействие его с сервером мы сделаем с использованием [flask](http://flask.pocoo.org... | github_jupyter |
<a href="https://colab.research.google.com/github/JimKing100/DS-Unit-2-Kaggle-Challenge/blob/master/Kaggle_Challenge_Assignment_Submission5.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
# Installs
%%capture
!pip install --upgrade category_enco... | github_jupyter |
```
import numpy as np
import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import pickle
# Read in an image
image = mpimg.imread('signs_vehicles_xygrad.png')
def abs_sobel_thresh(img, orient='x', sobel_kernel=3, thresh=(0, 255)):
# Apply the following steps to img
# 1) Convert to grays... | github_jupyter |
```
import numpy as np
import matplotlib.pyplot as plt
import numba
from tqdm import tqdm
import eitest
```
# Data generators
```
@numba.njit
def event_series_bernoulli(series_length, event_count):
'''Generate an iid Bernoulli distributed event series.
series_length: length of the event series
event_cou... | github_jupyter |
## The Analysis of The Evolution of The Russian Comedy. Part 3.
In this analysis,we will explore evolution of the French five-act comedy in verse based on the following features:
- The coefficient of dialogue vivacity;
- The percentage of scenes with split verse lines;
- The percentage of scenes with split rhymes;
- ... | github_jupyter |
# Lalonde Pandas API Example
by Adam Kelleher
We'll run through a quick example using the high-level Python API for the DoSampler. The DoSampler is different from most classic causal effect estimators. Instead of estimating statistics under interventions, it aims to provide the generality of Pearlian causal inference.... | github_jupyter |
# Welcome to the Datenguide Python Package
Within this notebook the functionality of the package will be explained and demonstrated with examples.
### Topics
- Import
- get region IDs
- get statstic IDs
- get the data
- for single regions
- for multiple regions
## 1. Import
**Import the helper functions 'g... | github_jupyter |
```
pip install pandera
pip install gcsfs
import os
import pandas as pd
from google.cloud import storage
serviceAccount = '/content/Chave Ingestao Apache.json'
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = serviceAccount
#leitura do arquivo em JSON
df = pd.read_json(r'gs://projeto-final-grupo09/entrada_dados/Projeto F... | github_jupyter |
# Chapter 4
`Original content created by Cam Davidson-Pilon`
`Ported to Python 3 and PyMC3 by Max Margenot (@clean_utensils) and Thomas Wiecki (@twiecki) at Quantopian (@quantopian)`
______
## The greatest theorem never told
This chapter focuses on an idea that is always bouncing around our minds, but is rarely ma... | github_jupyter |
# PTN Template
This notebook serves as a template for single dataset PTN experiments
It can be run on its own by setting STANDALONE to True (do a find for "STANDALONE" to see where)
But it is intended to be executed as part of a *papermill.py script. See any of the
experimentes with a papermill script to get sta... | github_jupyter |
```
%matplotlib inline
```
Neural Networks
===============
Neural networks can be constructed using the ``torch.nn`` package.
Now that you had a glimpse of ``autograd``, ``nn`` depends on
``autograd`` to define models and differentiate them.
An ``nn.Module`` contains layers, and a method ``forward(input)`` that
ret... | 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 2020 Erik Härkönen. All rights reserved.
# This file is licensed to you under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License. You may obtain a copy
# of the License at http://www.apache.org/licenses/LICENSE-2.0
# Unless required by app... | github_jupyter |
# Importing Dependencies
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import pandas_datareader
import pandas_datareader.data as web
import datetime
from sklearn.preprocessing import MinMaxScaler
from keras.models import Sequential
from keras.layers import Dense,LS... | github_jupyter |
# Hyperparameter tuning with Cloud AI Platform
**Learning Objectives:**
* Improve the accuracy of a model by hyperparameter tuning
```
import os
PROJECT = 'qwiklabs-gcp-faf328caac1ef9a0' # REPLACE WITH YOUR PROJECT ID
BUCKET = 'qwiklabs-gcp-faf328caac1ef9a0' # REPLACE WITH YOUR BUCKET NAME
REGION = 'us-east1' # REP... | github_jupyter |
# Köhn
In this notebook I replicate Koehn (2015): _What's in an embedding? Analyzing word embeddings through multilingual evaluation_. This paper proposes to i) evaluate an embedding method on more than one language, and ii) evaluate an embedding model by how well its embeddings capture syntactic features. He uses an ... | github_jupyter |
```
# In this exercise you will train a CNN on the FULL Cats-v-dogs dataset
# This will require you doing a lot of data preprocessing because
# the dataset isn't split into training and validation for you
# This code block has all the required inputs
import os
import zipfile
import random
import tensorflow as tf
from t... | github_jupyter |
```
# Confidence interval and bias comparison in the multi-armed bandit
# setting of https://arxiv.org/pdf/1507.08025.pdf
import numpy as np
import pandas as pd
import scipy.stats as stats
import time
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set(style='white', palette='colorblind', c... | github_jupyter |
# Transfer Learning Template
```
%load_ext autoreload
%autoreload 2
%matplotlib inline
import os, json, sys, time, random
import numpy as np
import torch
from torch.optim import Adam
from easydict import EasyDict
import matplotlib.pyplot as plt
from steves_models.steves_ptn import Steves_Prototypical_Network
... | github_jupyter |
<a href="https://colab.research.google.com/github/s-mostafa-a/pytorch_learning/blob/master/simple_generative_adversarial_net/MNIST_GANs.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
import torch
from torchvision.transforms import ToTensor, Nor... | github_jupyter |
```
import pandas as pd
import numpy as np
import os
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import seaborn
def filterOutlier(data_list,z_score_threshold=3.5):
"""
Filters out outliers using the modified Z-Score method.
"""
# n = len(data_list)
# z_score_threshold = (n-1)/np.sqrt(n)
data ... | github_jupyter |
# Matrix
> Marcos Duarte
> Laboratory of Biomechanics and Motor Control ([http://demotu.org/](http://demotu.org/))
> Federal University of ABC, Brazil
A matrix is a square or rectangular array of numbers or symbols (termed elements), arranged in rows and columns. For instance:
$$
\mathbf{A} =
\begin{bmatrix}
... | github_jupyter |
<a href="https://colab.research.google.com/github/mzkhan2000/KG-Embeddings/blob/main/embedding_word_clusters2.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
# Python program to generate embedding (word vectors) using Word2Vec
# importing neces... | github_jupyter |
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
dataset1=pd.read_csv('general_data.csv')
dataset1.head()
dataset1.columns
dataset1
dataset1.isnull()
dataset1.duplicated()
dataset1.drop_duplicates()
dataset3=dataset1[['Age','DistanceFromHome','Education','MonthlyIncome', 'NumCompaniesWorked', ... | github_jupyter |
# Convolutional Networks
So far we have worked with deep fully-connected networks, using them to explore different optimization strategies and network architectures. Fully-connected networks are a good testbed for experimentation because they are very computationally efficient, but in practice all state-of-the-art res... | github_jupyter |
# Pre-processing and analysis for one-source with distance 25
## Load or create R scripts
```
get.data <- dget("get_data.r") #script to read data files
get.pars <- dget("get_pars.r") #script to extract relevant parameters from raw data
get.mv.bound <- dget("get_mvbound.r") #script to look at movement of boundary acro... | github_jupyter |
# About
此笔记包含了以下内容:
* keras 的基本使用
* 组合特征
* 制作dataset
* 模型的存取(2种方式)
* 添加检查点
```
import tensorflow as tf
from tensorflow.keras import layers
import numpy as np
import matplotlib.pyplot as plt
import math
from tensorflow.keras.utils import plot_model
import os
# fea_x = [i for i in np.arange(0, math.pi * 2.0, 0.01)]
# ... | github_jupyter |
# Advent of Code 2016
```
data = open('data/day_1-1.txt', 'r').readline().strip().split(', ')
class TaxiCab:
def __init__(self, data):
self.data = data
self.double_visit = []
self.position = {'x': 0, 'y': 0}
self.direction = {'x': 0, 'y': 1}
self.grid = {i: {j: 0 for j ... | github_jupyter |
# [Strings](https://docs.python.org/3/library/stdtypes.html#text-sequence-type-str)
```
my_string = 'Python is my favorite programming language!'
my_string
type(my_string)
len(my_string)
```
## Respecting [PEP8](https://www.python.org/dev/peps/pep-0008/#maximum-line-length) with long strings
```
long_story = ('Lorem... | github_jupyter |
# FAQ
## I have heard of autoML and automated feature engineering, how is this different?
AutoML targets solving the problem once the labels or targets one wants to predict are well defined and available. Feature engineering focuses on generating features, given a dataset, labels, and targets. Both assume that the t... | github_jupyter |
# ADVANCED TEXT MINING
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---
## WEEK 02-2. Python 자료구조 이해하기
- 텍스트 데이터를 다루기 위한 Python 자료구조에 대해 다룹니다.
---
### 1. 리... | github_jupyter |
# Gradient Checking
Welcome to the final assignment for this week! In this assignment you will learn to implement and use gradient checking.
You are part of a team working to make mobile payments available globally, and are asked to build a deep learning model to detect fraud--whenever someone makes a payment, you w... | github_jupyter |
# Code along 4
## Scale, Standardize, or Normalize with scikit-learn
### När ska man använda MinMaxScaler, RobustScaler, StandardScaler, och Normalizer
### Attribution: Jeff Hale
### Varför är det ofta nödvändigt att genomföra så kallad variable transformation/feature scaling det vill säga, standardisera, normalisera... | github_jupyter |
# Tutorial 2. Solving a 1D diffusion equation
```
# Document Author: Dr. Vishal Sharma
# Author email: sharma_vishal14@hotmail.com
# License: MIT
# This tutorial is applicable for NAnPack version 1.0.0-alpha4
```
### I. Background
The objective of this tutorial is to present the step-by-step solution of a 1D diffus... | github_jupyter |
# lesson goals
* Intro to markdown, plain text-based syntax for formatting docs
* markdown is integrated into the jupyter notebook
## What is markdown?
* developed in 2004 by John Gruber
- a way of formatting text
- a perl utility for converting markdown into html
**plain text files** have many advantages of... | github_jupyter |
```
import tensorflow as tf
from tensorflow.keras.callbacks import TensorBoard
import os
import matplotlib.pyplot as plt
import numpy as np
import random
import cv2
import time
training_path = "fruits-360_dataset/Training"
test_path = "fruits-360_dataset/Test"
try:
STATS = np.load("stats.npy", allow_pickle=True... | github_jupyter |
# <span style="color:Maroon">Trade Strategy
__Summary:__ <span style="color:Blue">In this code we shall test the results of given model
```
# Import required libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os
np.random.seed(0)
import warnings
warnings.filterwarnings('ignore')
#... | github_jupyter |
```
import numpy as np
import math
import matplotlib.pyplot as plt
input_data = np.array([math.cos(x) for x in np.arange(200)])
plt.plot(input_data[:50])
plt.show
X = []
Y = []
size = 50
number_of_records = len(input_data) - size
for i in range(number_of_records - 50):
X.append(input_data[i:i+size])
Y.append(input... | github_jupyter |
# Monte Carlo Integration with Python
## Dr. Tirthajyoti Sarkar ([LinkedIn](https://www.linkedin.com/in/tirthajyoti-sarkar-2127aa7/), [Github](https://github.com/tirthajyoti)), Fremont, CA, July 2020
---
### Disclaimer
The inspiration for this demo/notebook stemmed from [Georgia Tech's Online Masters in Analytics (... | github_jupyter |
This illustrates the datasets.make_multilabel_classification dataset generator. Each sample consists of counts of two features (up to 50 in total), which are differently distributed in each of two classes.
Points are labeled as follows, where Y means the class is present:
| 1 | 2 | 3 | Color |
|--- |--- |--- |--... | github_jupyter |
Log the concentrations to and learn the models for CaCO3 again to avoid 0 happen in the prediction.
```
import numpy as np
import pandas as pd
import dask.dataframe as dd
import matplotlib.pyplot as plt
import seaborn as sns
plt.style.use('ggplot')
#plt.style.use('seaborn-whitegrid')
plt.style.use('seaborn-colorblin... | github_jupyter |
[Table of Contents](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/table_of_contents.ipynb)
# Kalman Filter Math
```
#format the book
%matplotlib inline
from __future__ import division, print_function
from book_format import load_style
load_style()
```
If you've gotten th... | github_jupyter |
# Multiple linear regression
In many data sets there may be several predictor variables that have an effect on a response variable.
In fact, the *interaction* between variables may also be used to predict response.
When we incorporate these additional predictor variables into the analysis the model is called *mult... | github_jupyter |
# Generative Adversarial Network
In this notebook, we'll be building a generative adversarial network (GAN) trained on the MNIST dataset. From this, we'll be able to generate new handwritten digits!
GANs were [first reported on](https://arxiv.org/abs/1406.2661) in 2014 from Ian Goodfellow and others in Yoshua Bengio'... | github_jupyter |
# Intro to Machine Learning with Classification
## Contents
1. **Loading** iris dataset
2. Splitting into **train**- and **test**-set
3. Creating a **model** and training it
4. **Predicting** test set
5. **Evaluating** the result
6. Selecting **features**
This notebook will introduce you to Machine Learning and class... | github_jupyter |
420-A52-SF - Algorithmes d'apprentissage supervisé - Hiver 2020 - Spécialisation technique en Intelligence Artificielle - Mikaël Swawola, M.Sc.
<br/>
<br/>
**Objectif:** cette séance de travaux pratique est consacrée à la mise en oeuvre de l'ensemble des con... | github_jupyter |
<a href="https://colab.research.google.com/github/keirwilliamsxyz/keirxyz/blob/main/Multi_Perceptor_VQGAN_%2B_CLIP_%5BPublic%5D.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Multi-Perceptor VQGAN + CLIP (v.3.2021.11.29)
by [@remi_durant](https:/... | github_jupyter |
```
# Copyright 2021 Google LLC
#
# 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 writi... | github_jupyter |
# WikiPathways and py4cytoscape
## Yihang Xin and Alex Pico
## 2020-11-10
WikiPathways is a well-known repository for biological pathways that provides unique tools to the research community for content creation, editing and utilization [@Pico2008].
Python is an interpreted, high-level and general-purpose programming... | github_jupyter |
# Plotting with Matplotlib
## What is `matplotlib`?
* `matplotlib` is a 2D plotting library for Python
* It provides quick way to visualize data from Python
* It comes with a set plots
* We can import its functions through the command
```Python
import matplotlib.pyplot as plt
```
```
import numpy as np
import matpl... | github_jupyter |
# Classes
For more information on the magic methods of pytho classes, consult the docs: https://docs.python.org/3/reference/datamodel.html
```
class DumbClass:
""" This class is just meant to demonstrate the magic __repr__ method
"""
def __repr__(self):
""" I'm giving this method a docstring
... | github_jupyter |
# Estimation on real data using MSM
```
from consav import runtools
runtools.write_numba_config(disable=0,threads=4)
%matplotlib inline
%load_ext autoreload
%autoreload 2
# Local modules
from Model import RetirementClass
import figs
import SimulatedMinimumDistance as SMD
# Global modules
import numpy as np
import p... | github_jupyter |
<a href="https://colab.research.google.com/github/clemencia/ML4PPGF_UERJ/blob/master/Exemplos_DR/Exercicios_DimensionalReduction.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
#Mais Exercícios de Redução de Dimensionalidade
Baseado no livro "Pytho... | github_jupyter |
## Ejemplos aplicaciones de las distribuciones de probabilidad
## Ejemplo Binomial
Un modelo de precio de opciones, el cual intente modelar el precio de un activo $S(t)$ en forma simplificada, en vez de usar ecuaciones diferenciales estocásticas. De acuerdo a este modelo simplificado, dado el precio del activo actual... | github_jupyter |
<a href="https://colab.research.google.com/github/sanjaykmenon/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module3-databackedassertions/Sanjay_Krishna_LS_DS_113_Making_Data_backed_Assertions_Assignment.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>... | github_jupyter |
# Working with Pytrees
[](https://colab.research.google.com/github/google/jax/blob/main/docs/jax-101/05.1-pytrees.ipynb)
*Author: Vladimir Mikulik*
Often, we want to operate on objects that look like dicts of arrays, or lists of lists of dicts... | github_jupyter |
<a href="https://colab.research.google.com/github/JohnParken/iigroup/blob/master/pycorrector_threshold_1.1.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
### 准备工作
```
from google.colab import drive
drive.mount('/content/drive')
import os
os.chdi... | github_jupyter |
```
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import requests
import time
from scipy.stats import linregress
import psycopg2
from sqlalchemy import create_engine, MetaData, Table, Column, Integer, String, Float
from api_keys import client_id
from twitch import TwitchClient
from pprint impor... | github_jupyter |
```
import CNN2Head_input
import tensorflow as tf
import numpy as np
SAVE_FOLDER = '/home/ubuntu/coding/cnn/multi-task-learning/save/current'
_, smile_test_data = CNN2Head_input.getSmileImage()
_, gender_test_data = CNN2Head_input.getGenderImage()
_, age_test_data = CNN2Head_input.getAgeImage()
def eval_smile_gend... | github_jupyter |
```
#import libraries
import numpy as np
import pandas as pd
print('The pandas version is {}.'.format(pd.__version__))
from pandas import read_csv
from random import random
import sklearn
print('The scikit-learn version is {}.'.format(sklearn.__version__))
from sklearn.model_selection import train_test_split, cross_v... | github_jupyter |
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