code stringlengths 38 801k | repo_path stringlengths 6 263 |
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# + [markdown] id="JDfSG9_9dZ9M"
# # Programa principal
# + [markdown] id="V... | Bosco Domingo, Luis de Marcos - P1.ipynb |
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import multiprocessing
def cube(x):
return x**3
... | parallel processing play.ipynb |
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import numpy as np
import pandas as pd
# ![1. Data Fr... | 1_Data_Frame/9_Header.ipynb |
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import sys
sys.version
import pandas as pd
impor... | notebook/Untitled.ipynb |
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# + id="8Xdmm79IChoP" colab_type="code" colab={}
import pandas as pd
import s... | Jupyter Notebook/Jupyter Notebok/Final Metrics Correlation/Metric 1,2 to 3,4/Jacoco/Collection/Collection 4.2.ipynb |
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# ### Checkbox
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from PyQt5 import QtCore, QtGui, Q... | Day 2.ipynb |
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# # 推測統計の基本
# ## 母集団と標本
# ### 標本の抽出方法
# +
import nu... | notebook/chap04.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | NB_tests.ipynb |
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# <table> <tr>
# <td style="background-color:... | bronze/B56_Quantum_Teleportation.ipynb |
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# name: python37564bitdeeplearningcond... | notebooks/Prediction.ipynb |
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from sklearn.datasets import load_iris
from sklearn.mo... | codecheatsheet/split_training_and_test_data.ipynb |
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# NOTE: To get files for this assignment # 2, run ... | IR Assignment 2 v3.1 .ipynb |
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import modcell as mods
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import sys
sys.path.appen... | notebooks/compile.ipynb |
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# # Name
# Submitting a Cloud Machine Learning Engine ... | components/gcp/ml_engine/train/sample.ipynb |
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# ![Self Check Exercises check mark image](files/art/c... | examples/ch03/snippets_ipynb/03_13selfcheck.ipynb |
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# + [markdown] id="MlOO1FiPSeGC"
# # Import Libraries
# + id="lF2vmbIpFa1L"
... | quickstart/Datacrunch_Cross_Validation.ipynb |
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# ###### Import libraries
import numpy as np
import p... | Machine Learning Algorithms/a. Linear Regression/other works/Linear Regression Datasets(test&train)/Study Assignment-1.ipynb |
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# + [markdown] button=false new_sheet=false run_contro... | docs/beta/notebooks/Parser.ipynb |
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# name: python392jvsc74a57bd0ffdb161abba9b4c6ed90ea70f14a998c... | notebooks/viz_exact.ipynb |
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import pandas as pd
import numpy as np
from sklea... | task1_modelling.ipynb |
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# a simple cnn model to separate noisy images from... | .ipynb_checkpoints/simple_cnn_noisy_clean_lp_classification-checkpoint.ipynb |
# <font size="10"><b><center>Heterogeneity and Macro Modeling</center></b></font>
# <font size="10"><b><center>In Policymaking Institutions</center></b></font>
# <br><br>
# <font size="6"><b><center><NAME></center></b></font>
# <font size="6"><b><center>Johns Hopkins University</center></b></font>
# <br><br>
# <font si... | Hetero-And-Macro/Hetero-And-Macro.ipynb |
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# + id="rqad6cNyIsR8" colab_type="code" colab={} executionInfo={"status": "ok... | dw_matrix_three/day2.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Loop_Statement.ipynb |
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import numpy as np
from sklearn.base import BaseEs... | notebooks/uncategorized/derivative/rbf_derivative_speedup.ipynb |
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# # Handling NaN values
# When analysing t... | docs/40_tabular_data_wrangling/handling_NaNs.ipynb |
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# <a href="https://colab... | Operations and Expressions in Python.ipynb |
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# # Analyze Performance
# %load_ext autoreload
# %aut... | experiment/analyze-performance.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | pycaret_ts_univariate.ipynb |
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# # 机器学习纳米学位
# ## 非监督学习
# ## 项目 3: 创建用户分类
# 欢迎来到机器学习工... | Project4_Unsupervised_learning/project/customer_segments.ipynb |
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import numpy as np
import os
from copy import dee... | rl_agent/generate_data.ipynb |
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... | neural_networks_tutorial.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Model testing/Model1_Galaxy_classification_sankalpa_v3.ipynb |
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from SmartAnno.utils.ReviewRBInit import R... | SmartAnno/test/TestReviewRB.ipynb |
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from __future__ import print_function
#... | develop/2017-03-12-SG-TestRegressioneLineareTF.ipynb |
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# <!--BOOK_INFORMATION-->
# <img align="left" style="p... | 07-Control-Flow-Statements.ipynb |
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# # Missing value imputation: DropMissingData
#
#... | examples/imputation/DropMissingData.ipynb |
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# <!--NAVIGATION-->
# < [Widgets Even... | notebooks/05.01-OPTIONAL-Widget_Events_2.ipynb |
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# # Starting Working on Pandas and Data Ana... | Day_25/college_salaries.ipynb |
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import random
students = {}
class Ranking_Syst... | Raiting System Neeeeew.ipynb |
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from sklearn.metrics import classification_report
... | binary_classifiers/DemoLSTM.ipynb |
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# Adding needed libraries and reading data
import ... | script/EDA.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Pertemuan_10.ipynb |
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# This notebook reproduces the computational examples ... | notebooks/1_Figs3-5.ipynb |
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# + [markdown] _uuid="2d74572580e24b09f3bbd0ec9d74bde0... | jaffe-with-resnet50.ipynb |
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# author: <NAME>, Ed.D., February 2019
# # *Pulling a... | Pulling and Processing PDFs .ipynb |
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from sklearn.preprocessing import... | regression/new code.ipynb |
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from your_lib.core import *
# # Parameter Ident... | index.ipynb |
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# + [markdown] graffitiCellId="id_ner1upo"
# # Countin... | concepts/Basic Algorithms/09 Counting Inversions.ipynb |
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import os
import numpy as np
# %matplotlib inline
from... | Chapter01/Chapter_1_Models_for_Time_Series_Analysis.ipynb |
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# + [markdown] colab_type="text" id="TWSHyGLvFHfl"
# #... | lecture_8/cnn_in_torch/low_level_pytorch.ipynb |
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# [View in Colaboratory]... | FactorizacionDiagonalizacion.ipynb |
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# ### Extrai informações da base de dados do EPM
impo... | util-code/01.notebook/1_get_data_sql.ipynb |
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# # CIFAR-10 Differential Attack
#
# ## Configuration
... | integration_tests/attacks/cifar10_differential_attack_with_corner_search.ipynb |
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import pandas as pd
import matplotlib.pyplot as plt
im... | visualization/pandas.ipynb |
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# Analysis based on wards
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from util... | segmentation/ProcessData_MAGNETIC_TILE_SURFACE_DEFECTS.ipynb |
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# # 作業 : (Kaggle)鐵達尼生存預測
# ***
# +
# 做完特徵工程前的所有準備
imp... | Day_030_HW.ipynb |
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import matplotlib.pyplot as plt
import pickle
import m... | figures.ipynb |
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import pandas as pd
import numpy as np
import requests... | notebooks/data_mining_test_data.ipynb |
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# Manipulação e tratamento das bases
i... | Notebooks cidades/Guarulhos_Durante.ipynb |
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# + [markdown] id="xTCDJCXJgjL8" colab_type="text"
# #RUN NN
# + id="Suu0L7j... | DeepLearning/DeepNetworks.ipynb |
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from os import path
from wordcloud import WordCloud
i... | jobs/job-desc-wordcloud.ipynb |
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import codecs
file = codecs.open("SastaSundar.html", ... | Python Web Scrapping.ipynb |
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# # Tutorial 07: Creating Custom Environments
#
# This... | tutorials/tutorial07_environments.ipynb |
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# + [markdown] id="Hc0XEe7S6Ft4" colab_type="text"
# # Seq2Seq with Attention... | colab/NMT-Seq2SeqWithAttention-de2en.ipynb |
# -*- coding: utf-8 -*-
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# %load_ext autoreload
# %autoreload ... | notebooks/11_clean_preferred.ipynb |
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# pandas and numpy for data manipulation
import pa... | mykernel2.ipynb |
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# + [markdown] id="DjUA6S30k52h"
# ##### Copyright 2021 The TensorFlow Author... | site/en-snapshot/tfx/tutorials/tfx/penguin_tft.ipynb |
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import requests
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from bs4... | 09-homework/Billboard Hot 100 Scraping.ipynb |
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# # The Rastrigin function: plotting result... | Rastrigin_check.ipynb |
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# ### Comparing Regression Models
# In thi... | ml_models/comparing_regression_models.ipynb |
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# # S3 equal temperament
#
# 3C6 Section 3: equal temp... | S3_equal_temperament.ipynb |
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# # Predicting Credit Default
# +
# sudo ... | MLCONF2021/CreditDefault.ipynb |
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# # Compare SQL phenotype to R phenotype
#
# <div class="alert alert-blo... | aou_workbench_pooled_analyses/phenotype_exploration/compare_sql_phenotype_to_r_phenotype.ipynb |
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# # Target Connectivity
# # Configurable logging syst... | ipynb/deprecated/releases/ReleaseNotes_v16.12.ipynb |
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# + [markdown] id="MjG6VZL35yNF"
# # OPTION A
# + [markdown] id="t2xlS3sR6Oy... | Prueba_5_Raul_Vergel_Romero_Opcion_A.ipynb |
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# # Plotly Fun
# Jupyter Notebooks look quite interest... | plotly-tutorial.ipynb |
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# + [markdown] id="NA5FvNG-KdqJ" colab_type="text"
# ## finance.yahoo.co.jp
... | notebooks/web_scraping_yahoo_fin_ranking_table.ipynb |
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cell_file = '..... | NeuroML2/notebooks/Test_poolosyn.ipynb |
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# This notebook was prepared by [<NAME>](https://githu... | recursion_dynamic/knapsack_01/knapsack_challenge.ipynb |
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i... | .ipynb_checkpoints/Country_Happiness_Predictor-checkpoint.ipynb |
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i... | Preprocess/Stanford_CSV.ipynb |
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# # FloPy
#
# ### Lake Example
#
# First set the path ... | examples/Notebooks/flopy3_lake_example.ipynb |
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# + id="GDZTwH3tS9BM" colab_type="code" colab={"base_uri": "https://localhost... | m2_day2_visual.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Facial_detection_model.ipynb |
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i... | notebooks/000_data_inspection.ipynb |
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# + [markdown] id="tAbV8ljjT_fC" colab_type="text"
# # Introducition to Pytho... | Notebooks/python 2 - lists tuples dicts strings.ipynb |
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# name: python3710jvsc74a57bd0b3ba2566441a7c06988d0923437866b63cedc6... | exploratory/PlayerLogsRebounds.ipynb |
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# # More on python
# Python has many high-level builti... | lecture15/02_More_Python.ipynb |
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# <center><h1> Assignment I </h1><br> <h2>Linear Reg... | ml-course/assignment_1/dqn170000_assignment_1.ipynb |
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# + _uuid="8f2839f25d086af736a60e9eeb907d3b93b6e0e5" _... | big-mart-sales-prediction/big-mart-sales-prediction (1).ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="... | examples/Sequence Labeling: Pretrained BERT.ipynb |
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# # Creating a GRU model using Trax: Ungraded Lecture ... | Part3_Sequence_Models/C3_W2_lecture_nb_4_GRU.ipynb |
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