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```
%%sh
pip -q install sagemaker stepfunctions --upgrade
# Enter your role ARN
workflow_execution_role = ''
import boto3
import sagemaker
import stepfunctions
from stepfunctions import steps
from stepfunctions.steps import TrainingStep, ModelStep, EndpointConfigStep, EndpointStep, TransformStep, Chain
from stepfuncti... | github_jupyter |
# Module 10 - Regression Algorithms - Linear Regression
Welcome to Machine Learning (ML) in Python!
We're going to use a dataset about vehicles and their respective miles per gallon (mpg) to explore the relationships between variables.
The first thing to be familiar with is the data preprocessing workflow. Data need... | github_jupyter |
<a href="https://colab.research.google.com/github/isaacmg/task-vt/blob/biobert_finetune/drug_treatment_extraction/notebooks/BioBERT_RE.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Finetuning BioBERT for RE
This is a fine-tuning notebook that we... | github_jupyter |
```
%matplotlib inline
from matplotlib import style
style.use('fivethirtyeight')
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import datetime as dt
from sqlalchemy import inspect
```
# Reflect Tables into SQLAlchemy ORM
```
import sqlalchemy
from sqlalchemy.ext.automap import automap_base
fr... | github_jupyter |
# Mislabel detection using influence function with all of layers on Cifar-10, ResNet
### Author
[Neosapience, Inc.](http://www.neosapience.com)
### Pre-train model conditions
---
- made mis-label from 1 percentage dog class to horse class
- augumentation: on
- iteration: 80000
- batch size: 128
#### cifar-10 train d... | github_jupyter |
```
import os
os.chdir('..')
os.chdir('..')
print(os.getcwd())
import rsnapsim as rss
import numpy as np
os.chdir('rsnapsim')
os.chdir('interactive_notebooks')
import numpy as np
import matplotlib.pyplot as plt
import time
poi_strs, poi_objs, tagged_pois,raw_seq = rss.seqmanip.open_seq_file('../gene_files/H2B_with... | github_jupyter |
##### Copyright 2020 The TensorFlow Authors.
```
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | github_jupyter |
```
import pandas as pd
import os
import glob
raw_data_path = os.path.join('data', 'raw')
clean_filename = os.path.join('data', 'clean', 'data.csv')
```
# Read data
```
all_files = glob.glob(raw_data_path + "/top_songs_with_lyrics.csv")
raw_data = pd.concat(pd.read_csv(f) for f in all_files)
raw_data.head()
```
# Pr... | github_jupyter |
```
%%html
<link href="http://mathbook.pugetsound.edu/beta/mathbook-content.css" rel="stylesheet" type="text/css" />
<link href="https://aimath.org/mathbook/mathbook-add-on.css" rel="stylesheet" type="text/css" />
<style>.subtitle {font-size:medium; display:block}</style>
<link href="https://fonts.googleapis.com/css?fa... | github_jupyter |
```
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder
from sklearn.metrics import roc_curve
from sklearn.metrics import auc
from sklearn.metri... | github_jupyter |
## CIFAR 10
```
%matplotlib inline
%reload_ext autoreload
%autoreload 2
```
You can get the data via:
wget http://pjreddie.com/media/files/cifar.tgz
**Important:** Before proceeding, the student must reorganize the downloaded dataset files to match the expected directory structure, so that there is a dedicat... | github_jupyter |
# 1. Very simple 'programs'
## 1.1 Running Python from the command line
In order to test pieces of code we can run Python from the command line. In this Jupyter Notebook we are going to simulate this. You can type the commands in the fields and execute them.<br>
In the field type:<br>
`print('Hello, World')`<br>
Then p... | github_jupyter |
## Install packages and connect to Oracle
```
sc.install_pypi_package("sqlalchemy")
sc.install_pypi_package("pandas")
sc.install_pypi_package("s3fs")
sc.install_pypi_package("cx_Oracle")
sc.install_pypi_package("fsspec")
from sqlalchemy import create_engine
engine = create_engine('oracle://CMSDASHADMIN:4#X9#Veut#KSsU#... | github_jupyter |
# Generative Spaces (ABM)
In this workshop we will lwarn how to construct a ABM (Agent Based Model) with spatial behaviours, that is capable of configuring the space. This file is a simplified version of Generative Spatial Agent Based Models. For further information, you can find more advanced versions here:
* [Objec... | github_jupyter |
```
# from google.colab import drive
# drive.mount('/content/drive')
import torch.nn as nn
import torch.nn.functional as F
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import torch
import torchvision
import torchvision.transforms as transforms
from torch.utils.data import Dataset, DataLoader... | github_jupyter |
##### Copyright 2018 The TensorFlow Authors.
Licensed under the Apache License, Version 2.0 (the "License");
```
#@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.o... | github_jupyter |
# Pre-procesamiento de datos
## Candidaturas elegidas
Principales transformaciones:
- Selección de atributos
- Tratamiento de valores faltantes
```
import glob
import nltk
import re
import pandas as pd
from string import punctuation
df_deputadas_1... | github_jupyter |
```
import torch
from dataset import load_dataset
from basic_unet import UNet
import matplotlib.pyplot as plt
from rise import RISE
from pathlib import Path
from plot_utils import plot_image_row
from skimage.feature import canny
batch_size = 1
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
trai... | github_jupyter |
<a href="https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/TrOCR/Evaluating_TrOCR_base_handwritten_on_the_IAM_test_set.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
## Set-up environment
```
!pip install -q gi... | github_jupyter |
```
import os, sys
import torch
from transformers import BertModel, BertConfig
from greenformer import auto_fact
from itertools import chain
from os import path
import sys
def count_param(module, trainable=False):
if trainable:
return sum(p.numel() for p in module.parameters() if p.requires_grad)
else:... | github_jupyter |
# Implementing a one-layer Neural Network
We will illustrate how to create a one hidden layer NN
We will use the iris data for this exercise
We will build a one-hidden layer neural network to predict the fourth attribute, Petal Width from the other three (Sepal length, Sepal width, Petal length).
```
import matpl... | github_jupyter |
# From batch to online
## A quick overview of batch learning
If you've already delved into machine learning, then you shouldn't have any difficulty in getting to use incremental learning. If you are somewhat new to machine learning, then do not worry! The point of this notebook in particular is to introduce simple no... | github_jupyter |
#### Copyright 2017 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 writin... | github_jupyter |
```
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
%matplotlib inline
data_label = pd.read_csv("data(with_label).csv")
```
### 30 day death age
```
fig = plt.figure(figsize=(12,6))
sns.set_style('darkgrid')
ax = sns.violinplot(x="thirty_days", hue="gender", y="age",data=d... | github_jupyter |
# Logic: `logic.py`; Chapters 6-8
This notebook describes the [logic.py](https://github.com/aimacode/aima-python/blob/master/logic.py) module, which covers Chapters 6 (Logical Agents), 7 (First-Order Logic) and 8 (Inference in First-Order Logic) of *[Artificial Intelligence: A Modern Approach](http://aima.cs.berkele... | 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 |
# Classification algorithms
In the context of record linkage, classification refers to the process of dividing record pairs into matches and non-matches (distinct pairs). There are dozens of classification algorithms for record linkage. Roughly speaking, classification algorithms fall into two groups:
- **supervised... | github_jupyter |
# Deep Matrix Factorisation
Matrix factorization with deep layers
```
import sys
sys.path.append("../")
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import pandas as pd
from IPython.display import SVG, display
import matplotlib.pyplot as plt
import seaborn as sns
from reco.preprocess import ... | github_jupyter |
# AdaDelta compared to AdaGrad
Presented during ML reading group, 2019-11-12.
Author: Ivan Bogdan-Daniel, ibogdanidaniel@gmail.com
```
#%matplotlib notebook
%matplotlib inline
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
print(f'Numpy version: ... | github_jupyter |
# Exploratory Data Analysis of AllenSDK
```
# Only for Colab
#!python -m pip install --upgrade pip
#!pip install allensdk
```
## References
- [[AllenNB1]](https://allensdk.readthedocs.io/en/latest/_static/examples/nb/visual_behavior_ophys_data_access.html) Download data using the AllenSDK or directly from our Amazon... | github_jupyter |
# Consumption Equivalent Variation (CEV)
1. Use the model in the **ConsumptionSaving.pdf** slides and solve it using **egm**
2. This notebooks estimates the *cost of income risk* through the Consumption Equivalent Variation (CEV)
We will here focus on the cost of income risk, but the CEV can be used to estimate the ... | github_jupyter |
# Facial Expression Recognizer
```
#The OS module in Python provides a way of using operating system dependent functionality.
#import os
# For array manipulation
import numpy as np
#For importing data from csv and other manipulation
import pandas as pd
#For displaying images
import matplotlib.pyplot as plt
import m... | github_jupyter |
2017
Machine Learning Practical
University of Edinburgh
Georgios Pligoropoulos - s1687568
Coursework 4 (part 7)
### Imports, Inits, and helper functions
```
jupyterNotebookEnabled = True
plotting = True
coursework, part = 4, 7
saving = True
if jupyterNotebookEnabled:
#%load_ext autoreload
%reload_ext aut... | github_jupyter |
```
import re
import json
import pandas as pd
import numpy as np
from collections import deque
```
## Process dataset
```
base_folder = "../movies-dataset/"
movies_metadata_fn = "movies_metadata.csv"
credits_fn = "credits.csv"
links_fn = "links.csv"
```
## Process movies_metadata data structure/schema
```
metadat... | github_jupyter |
```
import sympy as sp
import numpy as np
x = sp.symbols('x')
p = sp.Function('p')
l = sp.Function('l')
poly = sp.Function('poly')
p3 = sp.Function('p3')
p4 = sp.Function('p4')
```
# Introduction
Last time we have used Lagrange basis to interpolate polynomial. However, it is not efficient to update the interpolating ... | github_jupyter |
```
import numpy as np, pandas as pd, matplotlib.pyplot as plt
import os
import seaborn as sns
sns.set()
root_path = r'C:\Users\54638\Desktop\Cannelle\Excel handling'
input_path = os.path.join(root_path, "input")
output_path = os.path.join(root_path, "output")
%%time
# this line magic function should always be put on ... | github_jupyter |
# fuzzy_pandas examples
These are almost all from [Max Harlow](https://twitter.com/maxharlow)'s [awesome NICAR2019 presentation](https://docs.google.com/presentation/d/1djKgqFbkYDM8fdczFhnEJLwapzmt4RLuEjXkJZpKves/) where he demonstrated [csvmatch](https://github.com/maxharlow/csvmatch), which fuzzy_pandas is based on.... | github_jupyter |
<h1>Demand forecasting with BigQuery and TensorFlow</h1>
In this notebook, we will develop a machine learning model to predict the demand for taxi cabs in New York.
To develop the model, we will need to get historical data of taxicab usage. This data exists in BigQuery. Let's start by looking at the schema.
```
impo... | github_jupyter |
# TV Script Generation
In this project, you'll generate your own [Seinfeld](https://en.wikipedia.org/wiki/Seinfeld) TV scripts using RNNs. You'll be using part of the [Seinfeld dataset](https://www.kaggle.com/thec03u5/seinfeld-chronicles#scripts.csv) of scripts from 9 seasons. The Neural Network you'll build will ge... | github_jupyter |
# Deterministic point jet
```
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.pylab as pl
```
\begin{equation}
\partial_t \zeta = \frac{\zeta_{jet}}{\tau} - \mu \zeta + \nu_\alpha \nabla^{2\alpha} - \beta \partial_x \psi - J(\psi, \zeta) \zeta
\end{equation}
Here $\zeta_... | github_jupyter |
# Building Autonomous Trader using mt5se
## How to setup and use mt5se
### 1. Install Metatrader 5 (https://www.metatrader5.com/)
### 2. Install python package Metatrader5 using pip
#### Use: pip install MetaTrader5 ... or Use sys package
### 3. Install python package mt5se using pip
#### Use: pip install mt5se ... | github_jupyter |
<a href="https://colab.research.google.com/github/Lambda-School-Labs/bridges-to-prosperity-ds-d/blob/SMOTE_model_building%2Ftrevor/notebooks/Modeling_off_original_data_smote_gridsearchcv.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
This notebook ... | github_jupyter |
##### Copyright 2019 The TensorFlow Hub Authors.
Licensed under the Apache License, Version 2.0 (the "License");
```
# Copyright 2019 The TensorFlow Hub Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
... | github_jupyter |
<a href="https://cognitiveclass.ai"><img src = "https://ibm.box.com/shared/static/9gegpsmnsoo25ikkbl4qzlvlyjbgxs5x.png" width = 400> </a>
<h1 align=center><font size = 5>Waffle Charts, Word Clouds, and Regression Plots</font></h1>
## Introduction
In this lab, we will learn how to create word clouds and waffle charts... | github_jupyter |
<h2>Factorization Machines - Movie Recommendation Model</h2>
Input Features: [userId, moveId] <br>
Target: rating <br>
```
import numpy as np
import pandas as pd
# Define IAM role
import boto3
import re
import sagemaker
from sagemaker import get_execution_role
# SageMaker SDK Documentation: http://sagemaker.readthed... | github_jupyter |
# The overview of the basic approaches to solving the Uplift Modeling problem
<br>
<center>
<a href="https://colab.research.google.com/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero_EN.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg">
</a>
<br>
<b><a hr... | github_jupyter |
```
s = 'abc'
s.upper()
# L E G B
# local
# enclosing
# global
# builtins
globals()
globals()['s']
s.upper()
dir(s)
s.title()
x = 'this is a bunch of words to show to people'
x.title()
for attrname in dir(s):
print attrname, s.attrname
for attrname in dir(s):
print attrname, getattr(s, attrname)
s.upper
getattr... | github_jupyter |
##### Copyright 2019 The TensorFlow Authors.
**IMPORTANT NOTE:** This notebook is designed to run as a Colab. Click the button on top that says, `Open in Colab`, to run this notebook as a Colab. Running the notebook on your local machine might result in some of the code blocks throwing errors.
```
#@title Licensed un... | github_jupyter |
```
# ###############################################
# ########## Default Parameters #################
# ###############################################
start = '2016-06-16 22:00:00'
end = '2016-06-18 00:00:00'
pv_nominal_kw = 5000 # There are 3 PV locations hardcoded at node 7, 8, 9
inverter_sizing = 1.05
inverter_q... | github_jupyter |
<a href="https://colab.research.google.com/github/ymoslem/OpenNMT-Tutorial/blob/main/2-NMT-Training.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
# Install OpenNMT-py 2.x
!pip3 install OpenNMT-py
```
# Prepare Your Datasets
Please make sure y... | github_jupyter |
```
try:
from openmdao.utils.notebook_utils import notebook_mode
except ImportError:
!python -m pip install openmdao[notebooks]
```
# NonlinearBlockGS
NonlinearBlockGS applies Block Gauss-Seidel (also known as fixed-point iteration) to the
components and subsystems in the system. This is mainly used to solve ... | github_jupyter |
```
#remove cell visibility
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>
Promijeni vidljivost ... | github_jupyter |
## Search algorithms within Optuna
In this notebook, I will demo how to select the search algorithm with Optuna. We will compare the use of:
- Grid Search
- Randomized search
- Tree-structured Parzen Estimators
- CMA-ES
We can select the search algorithm from the [optuna.study.create_study()](https://optuna.readth... | github_jupyter |
## Duplicated features
```
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
```
## Read Data
```
data = pd.read_csv('../UNSW_Train.csv')
data.shape
# check the presence of missing data.
# (there are no missing data in this dataset)
[col for col in data.columns if data[col].... | github_jupyter |
# Python Basics with Numpy (optional assignment)
Welcome to your first assignment. This exercise gives you a brief introduction to Python. Even if you've used Python before, this will help familiarize you with functions we'll need.
**Instructions:**
- You will be using Python 3.
- Avoid using for-loops and while-lo... | github_jupyter |
This notebook was prepared by [Donne Martin](https://github.com/donnemartin). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges).
# Solution Notebook
## Problem: Generate a list of primes.
* [Constraints](#Constraints)
* [Test Cases](#Test-Cases)
* [Algorithm](#Algor... | github_jupyter |
```
from __future__ import print_function
import matplotlib.pyplot as plt
%matplotlib inline
import SimpleITK as sitk
print(sitk.Version())
from myshow import myshow
# Download data to work on
%run update_path_to_download_script
from downloaddata import fetch_data as fdata
OUTPUT_DIR = "Output"
```
This section of t... | github_jupyter |
# BUSINESS ANALYTICS
You are the business owner of the retail firm and want to see how your company is performing. You are interested in finding out the weak areas where you can work to make more profit. What all business problems you can derive by looking into the data?
```
# Importing certain libraries
import pandas... | github_jupyter |
## Introduction
In real world, there exists many huge graphs that can not be loaded in one machine,
such as social networks and citation networks.
To deal with such graphs, PGL develops a Distributed Graph Engine Framework to
support graph sampling on large scale graph networks for distributed GNN training.
In thi... | github_jupyter |
# "[ML] What's the difference between a metric and a loss?"
- toc:true
- branch: master
- badges: false
- comments: true
- author: Peiyi Hung
- categories: [learning, machine learning]
In machine learning, we usually use two values to evaluate our model: a metric and a loss. For instance, if we are doing a binary cla... | github_jupyter |
# Canonical correlation analysis in python
In this notebook, we will walk through the solution to the basic algrithm of canonical correlation analysis and compare that to the output of implementations in existing python libraries `statsmodels` and `scikit-learn`.
```
import numpy as np
from scipy.linalg import sqrtm
... | github_jupyter |
```
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasRegressor
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import KFold
from sklearn.model_selection ... | github_jupyter |
## Homework 3 and 4 - Applications Using MRJob
```
# general imports
import os
import re
import sys
import time
import random
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# tell matplotlib not to open a new window
%matplotlib inline
# automatically reload modules
%reload_ext autoreload
%au... | github_jupyter |
# Debugging Numba problems
## Common problems
Numba is a compiler, if there's a problem, it could well be a "compilery" problem, the dynamic interpretation that comes with the Python interpreter is gone! As with any compiler toolchain there's a bit of a learning curve but once the basics are understood it becomes eas... | github_jupyter |
# Introduction to Strings
---
This notebook covers the topic of strings and their importance in the world of programming. You will learn various methods that will help you manipulate these strings and make useful inferences with them. This notebook assumes that you have already completed the "Introduction to Data Scie... | github_jupyter |
##### Copyright 2020 The TensorFlow Authors.
```
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | github_jupyter |
# Naive Bayes Classifier (Self Made)
### 1. Importing Libraries
```
import numpy as np
import matplotlib.pyplot as plt
import os
import pandas as pd
from sklearn.metrics import r2_score
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn import preprocessing
from... | github_jupyter |
```
import numpy as np
import pandas as pd
import pickle
import time
import itertools
import matplotlib
matplotlib.rcParams.update({'font.size': 17.5})
import matplotlib.pyplot as plt
%matplotlib inline
import sys
import os.path
sys.path.append( os.path.abspath(os.path.join( os.path.dirname('..') , os.path.pardir ))... | github_jupyter |
# Dense Sentiment Classifier
In this notebook, we build a dense neural net to classify IMDB movie reviews by their sentiment.
```
#load watermark
%load_ext watermark
%watermark -a 'Gopala KR' -u -d -v -p watermark,numpy,pandas,matplotlib,nltk,sklearn,tensorflow,theano,mxnet,chainer,seaborn,keras,tflearn,bokeh,gensim
... | github_jupyter |
# Basics of the DVR calculations with Libra
## Table of Content <a name="TOC"></a>
1. [General setups](#setups)
2. [Mapping points on multidimensional grids ](#mapping)
3. [Functions of the Wfcgrid2 class](#wfcgrid2)
4. [Showcase: computing energies of the HO eigenstates](#ho_showcase)
5. [Dynamics: computed with SOF... | github_jupyter |
# Predicting the Outcome of Cricket Matches
## Introduction
In this project, we shall build a model which predicts the outcome of cricket matches in the Indian Premier League using data about matches and deliveries.
### Data Mining:
* Season : 2008 - 2015 (8 Seasons)
* Teams : DD, KKR, MI, RCB, KXIP, RR, CSK (7... | github_jupyter |
Let's load the data from the csv just as in `dataset.ipynb`.
```
import pandas as pd
import numpy as np
raw_data_file_name = "../dataset/fer2013.csv"
raw_data = pd.read_csv(raw_data_file_name)
```
Now, we separate and clean the data a little bit. First, we create an array of only the training data. Then, we create a... | github_jupyter |
# Step 2 - Data Wrangling Raw Data in Local Data Lake to Digestable Data
Loading, merging, cleansing, unifying and wrangling Oracle OpenWorld & CodeOne Session Data from still fairly raw JSON files in the local datalake.
The gathering of raw data from the (semi-)public API for the Session Catalog into a local data ... | github_jupyter |
Deep Learning Models -- A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks.
- Author: Sebastian Raschka
- GitHub Repository: https://github.com/rasbt/deeplearning-models
```
%load_ext watermark
%watermark -a 'Sebastian Raschka' -v -p tensorflow,numpy
`... | github_jupyter |
# SQL TO KQL Conversion (Experimental)
The `sql_to_kql` module is a simple converter to KQL based on [moz_sql_parser](https://github.com/DrDonk/moz-sql-parser).
It is an experimental feature built to help us convert a few queries but we
thought that it was useful enough to include in MSTICPy.
You must have msticpy in... | github_jupyter |
<a href="https://colab.research.google.com/github/oferbaharav/tally-ai-ds/blob/eda/Ofer_Spacy_NLP.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
import boto3
import dask.dataframe as dd
#from sagemaker import get_execution_role
import pandas as... | github_jupyter |
```
#hide
#skip
! [ -e /content ] && pip install -Uqq fastai # upgrade fastai on colab
#all_slow
#export
from fastai.basics import *
from fastai.learner import Callback
#hide
from nbdev.showdoc import *
#default_exp callback.azureml
```
# AzureML Callback
Track fastai experiments with the azure machine learning plat... | github_jupyter |
```
#Importing necessary dependencies
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
pd.set_option('display.max_columns',None)
df=pd.read_excel('Data_Train.xlsx')
df.head()
df.shape
```
## Exploratory data analysis
First we will try to find the missing values and we will ... | github_jupyter |
# Multiple Qubits & Entangled States
Single qubits are interesting, but individually they offer no computational advantage. We will now look at how we represent multiple qubits, and how these qubits can interact with each other. We have seen how we can represent the state of a qubit using a 2D-vector, now we will see ... | github_jupyter |
# A Transformer based Language Model from scratch
> Building transformer with simple building blocks
- toc: true
- branch: master
- badges: true
- comments: true
- author: Arto
- categories: [fastai, pytorch]
```
#hide
import sys
if 'google.colab' in sys.modules:
!pip install -Uqq fastai
```
In this notebook i'm... | github_jupyter |
## <span style="color:purple">ArcGIS API for Python: Real-time Person Detection</span>
<img src="../img/webcam_detection.PNG" style="width: 100%"></img>
## Integrating ArcGIS with TensorFlow Deep Learning using the ArcGIS API for Python
This notebook provides an example of integration between ArcGIS and deep learnin... | github_jupyter |
```
import tensorflow as tf
config = tf.compat.v1.ConfigProto(
gpu_options = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=0.8),
)
config.gpu_options.allow_growth = True
session = tf.compat.v1.Session(config=config)
tf.compat.v1.keras.backend.set_session(session)
import os
import warnings
warnings.filterw... | github_jupyter |
# Notebook to be used to Develop Display of Results
```
from importlib import reload
import pandas as pd
import numpy as np
from IPython.display import Markdown
# If one of the modules changes and you need to reimport it,
# execute this cell again.
import heatpump.hp_model
reload(heatpump.hp_model)
import heatpump.hom... | github_jupyter |
# Module 5 -- Dimensionality Reduction -- Case Study
# Import Libraries
**Import the usual libraries **
```
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
%matplotlib inline
```
# Data Set : Cancer Data Set
Features are computed from a digitized image of a fine needle a... | github_jupyter |
## CCNSS 2018 Module 5: Whole-Brain Dynamics and Cognition
# Tutorial 2: Introduction to Complex Network Analysis (II)
*Please execute the cell bellow in order to initialize the notebook environment*
```
!rm -rf data ccnss2018_students
!if [ ! -d data ]; then git clone https://github.com/ccnss/ccnss2018_students; \
... | github_jupyter |
<a href="https://colab.research.google.com/github/dlmacedo/starter-academic/blob/master/3The_ultimate_guide_to_Encoder_Decoder_Models_3_4.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
```
%%capture
!pip install -qq git+https://github.com/huggingfa... | github_jupyter |
# Step1: Create the Python Script
In the cell below, you will need to complete the Python script and run the cell to generate the file using the magic `%%writefile` command. Your main task is to complete the following methods for the `PersonDetect` class:
* `load_model`
* `predict`
* `draw_outputs`
* `preprocess_outpu... | github_jupyter |
# Think Bayes
Second Edition
Copyright 2020 Allen B. Downey
License: [Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/)
```
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import sys
IN_COLAB = ... | 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 |
# Software Carpentry
### EPFL Library, November 2018
## Program
| | 4 afternoons | 4 workshops |
| :-- | :----------- | :---------- |
| > | `Today` | `Unix Shell` |
| | Thursday 22 | Version Control with Git |
| | Tuesday 27 | Python I |
| | Thursday 29 | More Python |
## Why did you decide to attend this wo... | github_jupyter |
## Dependencies
```
import json, glob
from tweet_utility_scripts import *
from tweet_utility_preprocess_roberta_scripts import *
from transformers import TFRobertaModel, RobertaConfig
from tokenizers import ByteLevelBPETokenizer
from tensorflow.keras import layers
from tensorflow.keras.models import Model
```
# Load ... | github_jupyter |
# Simple Go-To-Goal for Cerus
The following code implements a simple go-to-goal behavior for Cerus. It uses a closed feedback loop to continuously asses Cerus' state (position and heading) in the world using data from two wheel encoders. It subsequently calculates the error between a given goal location and its curren... | github_jupyter |
# Chatbot Tutorial
- https://pytorch.org/tutorials/beginner/chatbot_tutorial.html
```
import torch
from torch.jit import script, trace
import torch.nn as nn
from torch import optim
import torch.nn.functional as F
import csv
import random
import re
import os
import unicodedata
import codecs
from io import open
import i... | github_jupyter |
# Work with Data
Data is the foundation on which machine learning models are built. Managing data centrally in the cloud, and making it accessible to teams of data scientists who are running experiments and training models on multiple workstations and compute targets is an important part of any professional data scien... | github_jupyter |
# Part 5: Competing Journals Analysis
In this notebook we are going to
* Load the researchers impact metrics data previously extracted (see parts 1-2-3)
* Get the full publications history for these researchers
* Use this new publications dataset to determine which are the most frequent journals the researchers hav... | github_jupyter |
# CAMS functions
```
def get_ADS_API_key():
""" Get ADS API key to download CAMS datasets
Returns:
API_key (str): ADS API key
"""
keys_path = os.path.join('/', '/'.join(
os.getcwd().split('/')[1:3]), 'adc-toolbox',
os.path.relpath('data/ke... | github_jupyter |
# SARK-110 Time Domain and Gating Example
Example adapted from: https://scikit-rf.readthedocs.io/en/latest/examples/networktheory/Time%20Domain.html
- Measurements with a 2.8m section of rg58 coax cable not terminated at the end
This notebooks demonstrates how to use scikit-rf for time-domain analysis and gating. A... | github_jupyter |
# Mouse Bone Marrow - merging annotated samples from MCA
```
import scanpy as sc
import numpy as np
import scipy as sp
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import rcParams
from matplotlib import colors
import seaborn as sb
import glob
import rpy2.rinterface_lib.callbacks
import logging
... | github_jupyter |
```
# importing the required libraries
import os
import numpy as np
import cv2
import matplotlib.pyplot as plt
%matplotlib inline
# function for reading the image
# this image is taken from a video
# and the video is taken from a thermal camera
# converting image from BGR to RGB
def read_image(image_path):
image... | github_jupyter |
### Topic Modelling Demo Code
#### Things I want to do -
- Identify a package to build / train LDA model
- Use visualization to explore Documents -> Topics Distribution -> Word distribution
```
!pip install pyLDAvis, gensim
import numpy as np
import pandas as pd
# Visualization
import matplotlib.pyplot as plt
from m... | github_jupyter |
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