code stringlengths 38 801k | repo_path stringlengths 6 263 |
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import twint
import gc
gc.collect()
import twint
import nest_asy... | other_social/twitter_page.ipynb |
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import os
import os.path
import itertools
import ... | network-analysis/compute-correlations.ipynb |
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# # Data Compression and Regression with Singular Valu... | Applications/SVD-DataCompress-Regression/SVD Data Compression and Regression.ipynb |
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library(data.table)
library(dplyr)
library(tidyr)
library(ggplot2)
libra... | notebooks/Figure1.ipynb |
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# + [markdown] deletable=true editable=true
# # Welcom... | tutorials/Step_1_Get_Data.ipynb |
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# + id="FZgP6jwmzFtZ" papermill={"duration": 0.024072,... | kaggle/k-nearest-evolution.ipynb |
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# ### Problem
# You are given an array of integers. Ea... | graphs/single_cycle_check.ipynb |
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import numpy as np
import utility
import matplotli... | src/notebooks/trips.ipynb |
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# + [markdown] nbsphinx="hidden"
# # Quantization of S... | quantization/noise_shaping.ipynb |
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# + [markdown] button=false new_sheet=false run_contro... | notebooks/Debugger.ipynb |
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# ## 2.1: Creating Interactive Plots
import numpy as ... | Section 2.ipynb |
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# # User Case
# PROFAB is a benchmarking platform tha... | test_file_2.ipynb |
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# ## PCA Projection with ECFP6 Fingerprint
# This not... | notebooks/PCA_projection_fingerprint.ipynb |
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import json # will be needed for saving preprocessing details... | research/loading_data.ipynb |
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# # Writing Testable Numerics Code
#
# Copyright (C) 2... | cleared-demos/error_and_fp/Writing Testable Numerics Code.ipynb |
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import numpy as np
import pandas as pd
import matp... | Projekty/Projekt1/Grupa2/PrzybylinskiPingielski/Milestone_1.ipynb |
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# + [markdown] button=false new_sheet=false ... | 8_Data Visualization with Python/2-2-Pie-Charts-Box-Plots-Scatter-Plots-and-Bubble-Plots-py-v2.0.ipynb |
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import copy
import h5py
import itertools
import numpy ... | sample1_modeler_questions.ipynb |
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# + [markdown] papermill={"duration": 0.067335, "end_t... | Notebooks/RadarCOVID-Report/Daily/RadarCOVID-Report-2021-05-20.ipynb |
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# + [markdown] colab_t... | old_figure3_create_plot.ipynb |
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# + id="m1AebNH3puZx"
import tensorflow as tf
# + colab={"base_uri": "https:... | single_perceptron.ipynb |
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#... | disambiguation/primary/model_dev/ASVe_IDs.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
fro... | Examples/Gradient Descent with Decaying Learning Rate.ipynb |
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# # Puzzle 1
# ... | 2021/day2/day2.ipynb |
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# # Lab 2
# ## Introduction
# This lab introduces slop... | notebooks/lab-02.ipynb |
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# # European Centre for Disease Prevention and Control... | notebooks/ECDC_GLOBAL.ipynb |
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# + [markdown] id="ariHTDRGlolu"
# # **Regression: Predict Fuel Efficiency `t... | regression.ipynb |
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# # \__init_subclass__()
#
# 重写\__init_subclass__方法， 先... | 基础/子类相关.ipynb |
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# https://github.com/nipy/nipype/blob/master/examples/... | notebooks/z_advanced_databases.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as p... | 02 Kernel-based Learning/Tutorial 05 - Support Vector Regression/main.ipynb |
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# # 1. Decision Tree
import pandas as pd
from sklearn... | A_5 Random Forest and Decision Tree.ipynb |
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# # Plotting a single ping example
# This script demon... | examples/jupyter notebooks/plot_single_ping_example.ipynb |
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# ## Load and select data
#
# sf_use have 20000 sample... | Step1-SimpleNBModel.ipynb |
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# # Net Surgery
#
# Caffe networks can be transformed ... | examples/net_surgery.ipynb |
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# # Triggering a Cloud Composer Pipeline with a Google... | courses/data-engineering/demos/composer_gcf_trigger/composertriggered.ipynb |
# +
# Code is from <NAME> et al,
# "Bayesian Modeling and Comptuation In Python"
# https://github.com/aloctavodia/BMCP/blob/master/Code/chp_3_5/splines.py
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
try:
from patsy import bs, dmatrix
except ModuleNotFoundError:
# %pip install -... | notebooks/book1/11/splines_basis_heatmap.ipynb |
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# # 1. Parameters
# + tags=["parameters"]... | evaluations/simulation/template-4-variants-comparison.ipynb |
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# # Local Installation
#
# **Prerequisites**
#
# - Non... | Year19-20/2019-06-24__GettingStarted/03_local_install.ipynb |
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import logging
logging.basicConfig(filename=u"main... | main/main(1).ipynb |
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# MOAI 2020 Body Morphometry AI Segmentation Online Ch... | Body Morphometry.ipynb |
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# ### scvi must b... | notebooks/02_integrate_scvi_revision.ipynb |
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import pandas
food_info = pandas.read_csv("food_info.c... | pandans/pandas_1.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Sistemas_de_recomendacao_de_filmes.ipynb |
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"""
There are people sitting in a circular fashion... | Python/circular_counter.ipynb |
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import pandas as pd
# +
# Read dataframe and show it
... | data analysis/notebooks/spatial_101/0103_spatial_analysis/idw-3d-and-mercury-concentrations-data-prep.ipynb |
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# imports
import pandas as pd
import numpy as np
impo... | notebooks/GeneralStats/radiant_dire_stats.ipynb |
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import pandas as pd
import numpy as np
results = pd.... | examples/scipy-2018-paper-examples/compare_results_mri.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | module1-decision-trees/221_assignment.ipynb |
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import os
os.environ['PYSPARK_PYTHON'] = '/opt/conda/b... | datafaucet/cli/templates/ingest/{{cookiecutter.project_name}}/src/daily.ipynb |
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# # hw3
#
# For this homework, you are a data scientis... | HW3.ipynb |
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job_id = 'raw_openmiir_baseline_chmean'
# +
import os... | Train OpenMIIR baseline ch_mean RAW.ipynb |
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# # linear regression
# find f(x) such most fits sampl... | regression/linear_regression/simple.ipynb |
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# # twee2vec
# https://github.com/KavelCortex/... | twee2vec_demo.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | nbs/PointNetClass.ipynb |
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# %matplotlib notebook
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# things we need for NLP
import nltk
from nltk.ste... | Chatbot2.ipynb |
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import pandas as pd
import matplotlib.pypl... | MTA Graphs.ipynb |
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# ## Reference
# - [Deep Learning with Keras](https://... | MLP/MINST_v5.ipynb |
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# + [markdown] colab_type="text" id="uFl5VYXPIY7D"
# #... | day04/Breast_Cancer_Demo.ipynb |
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# # Boosting to Uniformity
#
# In physical application... | notebooks/BoostingToUniformity.ipynb |
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# # Monte Carlo Methods
#
# In this notebook, you will... | monte-carlo/Monte_Carlo.ipynb |
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# + hidden="all" school_cell_uuid="b1517c11... | 04. 데이터 분석의 소개/01. 데이터 분석의 소개.ipynb |
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# Python 3
# Anchor extraction from html document
... | notebooks/BeautifulSoup_XML.ipynb |
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# # Retention Time Preidiction
#
# This notebook is p... | notebooks/tasks/4_DataSplit.ipynb |
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# + colab={"base_uri": "https://localhost:8080/", "hei... | 07_training/07c_export.ipynb |
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import numpy as np
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from nltk.clas... | stock.ipynb |
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# # cMLP Lagged VAR Demo
#
# - In this notebook, we tr... | cmlp_lorenz_demo.ipynb |
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# + hideCode=true hideOutput=true
import os, sys
try... | docs/synapse/userguides/storm_adv_vars.ipynb |
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# # Italy Crime Index web ... | italy_crime_index.ipynb |
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# <center>
# <img src="https://s3-api.us... | ML0101EN-RecSys-Content-Based-movies-py-v1.ipynb |
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# # Kaggle介绍
#
# 网址：[https://www.kagg... | Resources/Kaggle.ipynb |
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# # TF-IDF in digitised journals
#
# This notebook cal... | umdigitalstudio2019/tfidf_in_digitised_journals.ipynb |
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# + [markdown] colab_type="text" id="view-in-github"
# <a href="https://colab... | notebooks/function_space_linearization.ipynb |
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# Introduction to Python Programming
# ===
# ## Basic... | notebooks/0-introduction-to-python.ipynb |
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# %matplotlib inline
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# Copyright (c) Microsoft Corporation. All rights r... | how-to-use-azureml/deployment/deploy-multi-model/multi-model-register-and-deploy.ipynb |
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# ## Asset Pricing via Simulation
#
# #### <NAME>
imp... | day3/applications/asset_pricing/asset_pricing_simulation_with_ssy.ipynb |
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# ### ML
# 1. Datos. Detectar el tipo de problema:
# - Clasificación: (Logistic regression, SVC, KNN,Decission Tree C,Rrandom Forest Clas... | week10_ML_competition_pca_kmeans/day1_gridsearch_pipelines/gridsearch/esquema.ipynb |
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# # Copy items-Copy1.csv file into pandas dataframe an... | latent_dirichlet_allocation.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 02_basics/07_nn_implementation.ipynb |
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i... | simulation-visualization.ipynb |
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# ### Task -1
# +
mutiline_text = """It is a truth u... | Lesson01/Activity01/.ipynb_checkpoints/Student Activity 01 - Solutions-checkpoint.ipynb |
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# - scikit-image https://scikit-image.org
# - O... | ImageProcessing/1-image-pixel-binary.ipynb |
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# ### You will learn to use Scikit-Learn, a machine le... | hw1/hw1-multimodal-learning-scikit-learn.ipynb |
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# ### SKBL - JSON data occupation
# * GITHUB [salgo60... | Jupyter/.ipynb_checkpoints/SKBL yrken JSON-checkpoint.ipynb |
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#
# <br>
# @author: <NAME><br>
#
import r... | Jupyter Notebooks/MF_Simulation_PIR.ipynb |
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# # A short example of ctaplot functions
# + pycharm... | examples/notebooks/resolution_examples.ipynb |
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# Using a helper function to do Cross Validation a... | Chapter 5/5.0.2 Automatic Cross Validation.ipynb |
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# # 파일 읽고 쓰기
# # 파일 생성하기
f = open("새파일.txt",'w')
f.... | JumptoPython/Part_4_Program_IO/04-3_File_Read_and_Write.ipynb |
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# # Prediction using keras
# Let us import pandas to ... | prediction_using_keras.ipynb |
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# # Линейная регрессия и стохастический градиентный сп... | Coursera/Machine-learning-data-analysis/Course 2/Week_01/PA_linreg_stochastic_grad_descent.ipynb |
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#匯入lib
import pandas as pd
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impor... | Logistic Regression - using sklearn.ipynb |
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df = parse('pokemon_jay.csv')
species_count(df)
ma... | hw2/Untitled.ipynb |
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import os
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