code stringlengths 38 801k | repo_path stringlengths 6 263 |
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'''
import libraries and set print options
'''
import ... | synthetic_data/scripts/manual_data_cleaning.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | DSPT6_U2S1M2_JeffreyAsuncion_assignment.ipynb |
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# <div class="alert alert-block alert-info" style="mar... | PY0101EN-3-3-Functions.ipynb |
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from bs4 import BeautifulSoup
import reque... | ncaa-data-processing.ipynb |
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# # Imports
# +
import pandas as pd
import time
impor... | code/04_ELO_Model.ipynb |
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# # Euler Method
# The Euler method works by assuming ... | engsci211_ode3_euler.ipynb |
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# # Model Tuning
# > A Summary of lecture "Machine Lea... | _notebooks/2020-06-04-03-Model-Tuning.ipynb |
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# # Deviations from Normality
#
# _(plus python functi... | Investment Management/Course1/lab_105.ipynb |
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# General:
import tweepy # To consume Tw... | 6210_project_YufanYang_JiahaoZhao_YoumingZheng/code_collecting_data/homepage_tweets.ipynb |
# -*- coding: utf-8 -*-
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# # Strings
#
# Topics:
# ... | Julia/Notebooks/1. Introduction-to-Julia-main/1 - Strings.ipynb |
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list0 = [1,2,"3",4]
if "3" in list0:
print("있음")
... | nest_loop.ipynb |
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# <script async src="https://www.googletagmanager.com/... | IllinoisGRMHD/doc/Tutorial-IllinoisGRMHD__MoL_registration.ipynb |
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# # About: LDAP認証の設定
#
# ---
#
# MoodleのLDAP認証プラグインの設定... | Moodle-Simple/notebooks/211-LDAP認証の設定.ipynb |
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import easyib
api = easyib.REST()
# defau... | examples/examples.ipynb |
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# # Python Lambda Functions
# Anonymous, s... | Python Lambda Functions.ipynb |
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from matplotlib import pyplot as plt
import numpy ... | jupyter/tax.ipynb |
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# + [markdown] id="s8XtcgbGj5xN" colab_type="text"
# #Linear Regression for M... | Week 3/MNIST_Linear_Regression.ipynb |
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# default_exp ai_platform_constants
# +
#export
f... | ai_platform_constants.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# <h1... | example/pdenetgen-NN-PKF_burgers_learn-exogenous-closure.ipynb |
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# + [markdown] id="Y_WGyPRajc2P" colab_type="text"
# # MNIST Dynamic Filter C... | Chapter04/5. MNIST dynamic filter classification result.ipynb |
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# # T4 Time series
# ## Time series with elapsed time... | tutorials/T04_Time-series-Empty.ipynb |
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# # ... | 2021/Day 19.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Economics_Milestone5_Causal_ipynb.ipynb |
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# # Web-Scraping Project
#
# ### Preparing for Web-Scr... | USF_Web_Scraping_Project.ipynb |
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# # Classwork 4
#
# ### _<NAME>, <NAME>, <NAME>_:
#... | cw04-primes.ipynb |
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# %matplotlib... | 2018_06_Amsterdam/mne_notebook_2_evoked_data.ipynb |
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#Importing libraries
from __future__ import print_... | Regression-Predicting-a-real-valued-output-for-Petrol_Consumption.ipynb |
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# # Heap Class and Heap Operations
#
# The Heap_Class.... | DataStructures/Tree_DataStructures/HEAPS/About_Heap_Class_And_Operations.ipynb |
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import re
import folium
import numpy as np... | main.ipynb |
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# + [markdown] colab_type="text" id="pfbg_NxOEZ-k"
# #... | 09/.ipynb_checkpoints/SolutionExercise9-checkpoint.ipynb |
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# # Project 3
#
#
# # Movie Genre Classification
#
# C... | Exercises/P3-MovieGenrePrediction.ipynb |
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# + [markdown] heading_collapsed=true
# # EDA of proce... | ntbks/openFDA_drug_event_parsing/Exploring.ipynb |
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"""
1. Standard deviation.
A number that de... | 0.ML-Basics-to-pro-Python-Lab/.ipynb_checkpoints/2.StandardDeviation-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 04_Apply/US_Crime_Rates/Exercises.ipynb |
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# # WACV -- CityScapes
#
# ## 19 semantic classes
#
# ... | examples/inference/WACV-CS-segm.ipynb |
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import numpy as np
import pandas as pd
import mat... | pima- seed-19/sample generation.ipynb |
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# # `allcools mcds`
# + tags=["remove-cell"]
import s... | docs/allcools/command_line/allcools_mcds.ipynb |
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import pandas as pd
import numpy as np
import matp... | edas/.ipynb_checkpoints/Explore Kryptos Dataset-checkpoint.ipynb |
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#default_exp transfor... | nbs/04_transform.ipynb |
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import os,sys,inspect
currentdir = os.path.dirname(os.... | notebooks/Evaluation-of-measures-LensKit-100k.ipynb |
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# # Lab 2: Data Types
# Welcome to Lab 2!
#
# Last tim... | lab02/lab02.ipynb |
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# # 計算 sin(x)
import numpy as np
import matplotlib.py... | NCCU Applications of mathematics softwares/lesson_6_4.ipynb |
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# <center><i><img src="https://www.python.org/static/a... | IT/restart_server.ipynb |
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# Standard Imports and Extensions... | examples/StlPerfTest/StlJavaFortranComparison.ipynb |
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# + [markdown] id="wd-PuFkHXHAW" colab_type="text"
# Code from https://www.in... | Slides/Winter 2020/16) K-Nearest Neighbors/17_1_Nearest_Neighbors.ipynb |
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# <small><small><i>
# All the IPython Notebooks in **P... | 010_Python_Type_Conversion.ipynb |
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# # Collect data
# 1. Find yourself an data set that y... | homework/Week1-Assignment.ipynb |
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# #### imports
1
# +
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#########... | RefSeq-analysis/data_acquisition/genome_sequence_data/python_scripts/get_refseq_lncrna_seq.ipynb |
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import sys
import warnings
if not sys.warnoptions... | deep-learning/011bidirectional-lstm-seq2seq.ipynb |
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# # Density estimation ussing GMM
#
# This is an examp... | jupyter/EM_Gaussian_mixture.ipynb |
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import torch
import... | Courses/PyTorch for Deep Learning with Python/07 ANN/040_Linear_regression.ipynb |
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# # Creating the action client
# This time, we'll mak... | Modules/Module 6 - ROS Actions/4. Creating the ROS action client.ipynb |
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# # Task 5: Group Data Analysis
# ---
# In this noteb... | analysis/Germaine/Group Data Analysis.ipynb |
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# ModSim project 1
# +
# Configure Jupyter so figures... | code/Project1.2.ipynb |
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# # **Basic problem solution**
# imports
... | Notebooks/basic_graph_example.ipynb |
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# + colab={} colab_type="code" id="wPY4it_wHzvW"
impor... | intro-notebooks/single_layer_network.ipynb |
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from tensorflow import keras
from tensorflow.keras imp... | BCNcode/0_vibratioon_signal/1250/DNN/CNN_1250-015-512-y.ipynb |
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# ## Final Project: Linear Regression
#
# - We want to... | Final_Project/.ipynb_checkpoints/Final_Project-checkpoint.ipynb |
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# ## Populate MOF with given molecule and initialize L... | scripts/lammps/Diffusion-111.ipynb |
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# + id="0zFs256qPZi6"
import pandas as pd
import numpy as np
import matplotli... | code/Notebooks/fake_news_classification_inference.ipynb |
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# # IR-Reproducibility with Transferred Relevance Judg... | case-studies/relevance-label-transfer/src/main/jupyter/ir-reproducibility-with-transferred-relevance-judgments.ipynb |
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# # The Monty Hall problem
#
# The [Monty Hall problem... | notebooks/06/monty_hall.ipynb |
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# # Figures for fits to UHECR data
#
# Here, w... | uhecr_model/notebooks/gmf/fit_to_data/figures/figures_PAO_SBG.ipynb |
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# + [markdown] colab_type="text" id="aoxI3DOK9vm2"
# #... | 8_3_5_deeplearning_gan_sam.ipynb |
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# ____
#
# <center> <h1 style="background-... | Data Science Course/1. Programming/3. Python (with solutions)/Module 4 - Data Cleaning/Practice Solution/02-Data Cleaning - Outlier and Text Exercise - Solutions.ipynb |
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# +
import pandas as pd
import numpy as np
import os
i... | 1_downlaod_gwas_neale.ipynb |
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# # Issue Analysis
# +
import psycopg2
import pandas ... | templates/.ipynb_checkpoints/issues_template-checkpoint.ipynb |
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# # Deep Equals
#
# Write a function that determines i... | JavaScript/Python-Drills/06-Deep_Equals/Unsolved/Deep_Equals.ipynb |
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# + [markdown] colab_type="text" id="y00b5TQZnqs_"
# #... | image-classifier/Project_Image_Classifier_Project.ipynb |
# -*- coding: utf-8 -*-
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# Exam by <NAME>
# ## Problem 2
#
# Th... | Exam_1_Answers.ipynb |
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# # Convolutional Layer
# Visualize four filtered out... | 01_Convolution_Layer/Convolutional Layer.ipynb |
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# Using NumPy arrays enables you to express many kinds... | Vectorization_m03_demo03.ipynb |
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import math
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# # <img style="float: left; padding-right: 10px; widt... | docs/lectures/lecture03/notebook/cs109a_L3_Ex1_solutions.ipynb |
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# + [markdown] id="Ff_Jv8Ptu4lP"
#
# # INSTALLATION
# + colab={"base_uri": "... | Fairness_Survey/ALGORITHMS/EO/LawSchool.ipynb |
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# # 划分方式
# +
# 12666 imgs：
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# # 課題4 テキストデータ分析
# 配点
# - Q1, 1P
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# - Q3, 5... | ex4/ex4.ipynb |
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# # "Galfitting" with lenstronomy
# An example of usin... | lenstronomy_extensions/Notebooks/galfitting.ipynb |
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# ## 01 - ... | notebooks/01-00 Introduction to Python.ipynb |
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# # Exploring a Data Repository
#
# <br>Owner: **<NAME>** ([@... | Graveyard/Exploring_An_HSC_Data_Repo.ipynb |
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# clear all variables
for i in list(globals().keys... | python/1. CFAS Distribution and Correlation Figures.ipynb |
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# I want to write an equation that recreates the RC-as... | code/Scripts/clump-ladder.ipynb |
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# # Data Collection Using Spotify Web API
#
# ## Spoti... | .ipynb_checkpoints/anjunadeep-explorations-playlists-checkpoint.ipynb |
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# # JupyterHub Spawners
#
... | spawners.ipynb |
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from kh2lib.kh2lib import kh2lib
lib = kh2lib()
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... | notebookToHtml/biosignalsnotebooks_html_publish/Categories/Install/prepare_jupyter.ipynb |
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# # Python for Environmental Science Day 7
# ## Topics... | week_2/day_7_notebook.ipynb |
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# ### Read input data from... | textrank_summerization.ipynb |
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# # Homework 6, Part One: Lots and lots of questions a... | 06-homework/beer/.ipynb_checkpoints/Dataset ONE - Beer cans-checkpoint.ipynb |
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# + _uuid="2f0e779a6d98b9c9c06e2abe47f5428fa0e2c68c"
i... | notebooks/model/baseline-gridsearch.ipynb |