code stringlengths 38 801k | repo_path stringlengths 6 263 |
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# !pip install sentence_transformers
# !pi... | sem7/homework_7.ipynb |
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using TikzGraphs
using TikzPictures
using Graphs
... | Untitled.ipynb |
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import pandas as pd
import numpy as np
from model... | practica1/mamografias_dropna.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
fro... | Assignment7.ipynb |
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import glob
import math
import scicm
import numpy ... | images/.ipynb_checkpoints/Example_images-checkpoint.ipynb |
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import warnings
warnings.filterwarnings(action='ig... | MF_Base.ipynb |
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# name: python373jvsc74a57bd0210f9608a45c0278a... | wandb/run-20210517_205534-1c4rmzu2/tmp/code/main.ipynb |
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# # Copy Task Plots
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import matplotlib.pyplot as p... | notebooks/copy-task-plots.ipynb |
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# #1 美观并正确地书写Python语句
#
# ###书写的美观性
#
# 往往问题不仅是美观，还在于程... | Series_0_Python_Tutorials/S0EP2_Control_Flow_Data_Structure.ipynb |
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import torch
from torchvision import datasets
import n... | SVM/SVM.ipynb |
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# # Overview
# > overview of examples
# The examples ... | nbs/examples/example_overview.ipynb |
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# # Used car analysis
#
# We'll work with a dataset of... | ebay_car_sales/UsedCarAnalysis.ipynb |
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# Try setting OPM_NUM_THREADS=1.
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import glob
impo... | notebooks/hc_sig_cut_archived_tills_Fe.ipynb |
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# # Logistic Regression
#
# This function shows how to... | ch03_regression/08_logistic_regression.ipynb |
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import os
import numpy as np
import networkx as nx... | code/data_process/connectivity.ipynb |
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# %run -p ../train_cnf_disentangle_rl.py --data cifar1... | conditional/main_conditional_disentangle_cifar_bs8K_sratio_0_5_drop_0_5_rl_stdscale_15_run1.ipynb |
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import populartimes
import math
import numpy as np... | JRDN SurfPod Analysis.ipynb |
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from dask.distributed import Client
import dask.bag as... | Dask/word_frecuency_sort_dask.ipynb |
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# # Multi Agent DDPG Agent for Tennis Game (Report)
#
# ---... | Report.ipynb |
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# # Testing area for Exception in thread
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from th... | python/Tread exception.ipynb |
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# # "[OptimizationTheory] CH01. Introducti... | _notebooks/math/optimization-theory/ch01-introduction.ipynb |
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# # ... | stochastic_segmentation_networks.ipynb |
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# + _cell_guid="b1076dfc-b9ad-4769-8c92-a6c4dae69d19" ... | extension/examples/8570777.ipynb |
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import matplotlib.pyplot as plt
import numpy as n... | clinical/timelines.ipynb |
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# # Project 1
#
# ## Step 1: Open the `sat_sco... | _posts/project-1-sat-scores/project_1.ipynb |
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# # Part 1
import pandas as pd
households = pd.read_c... | carbon.ipynb |
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# + [markdown] colab_type="text" id="kR-4eNdK6lYS"
# D... | 2_fullyconnected.ipynb |
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# # T81-558: Applications of Deep Neural Netwo... | t81_558_class3_training.ipynb |
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# # P2P结构
#
# p2p(peer to peer)可以定义成终端之间通过直接交换来共享计算机资源... | 异步socket编程/p2p结构.ipynb |
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# # Code Reuse
# Let’s put what we learned about code... | Crash Course on Python/pygrams_notebooks/utf-8''C1M5L3_Code_Reuse.ipynb |
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# ## [[Stack Overflow] Gathering a sequenc... | notebooks/255_gather_unknown_length.ipynb |
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# +
from torch import Size
from rewards ... | CLEAN/Rewards/reward_profiling.ipynb |
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# ## Import pacakages
import numpy as np
import tenso... | MNIST.ipynb |
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import json
import pandas as pd
import numpy as np... | ETL_create_database.ipynb |
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# + [markdown] colab_type="text" id="UQWlGqS0o1ta"
# #... | CaseStudy/TelecomChurn/CaseStudy_Telecom_Churn_Prediction.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | day5/keras_mnist_v3_5layer_fc_dropout.ipynb |
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# # Rolling Update Tests
#
# Check rolling updates fun... | notebooks/rolling_updates.ipynb |
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# # Setup Code
# +
import pandas as pd
import matplot... | Jupyter/Class_ML_Path/03 Linear Regression/BasicRegression.ipynb |
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## This cell just imports necessary modules
# %pylab n... | mathematics/mm1/Lecture_1_Coordinate_Systems.ipynb |
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# # End-to-End Example #1
#
#... | sagemaker-python-sdk/1P_kmeans_highlevel/kmeans_mnist.ipynb |
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# # Beginning interactivity with tabular data: ipywidg... | week05/_prep_notebook_week04_old.ipynb |
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# ## Largest Rectangle
# +
# #!/bin/python3
import m... | contest/Stack & Queue - I (16-05-2021).ipynb |
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# # Programming Exercise 1: Linear Regression
#
# # In... | Machine Learning - Coursera/machine-learning-ex1/ex1.ipynb |
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# ## 재귀
# - 하나의 문제를 기본 단계와 재귀 단계로 나눔
# - 분할 정복법에서 이 개념... | Grokking-Algorithms/03.recursive.ipynb |
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import os
os.environ['CUDA_VISIBLE_DEVICES... | phoneme/parse-johor.ipynb |
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# + [markdown] id="zvI35BjxZiR_"
# # Decision Tree Cla... | Classification/Decision Tree/DecisionTreeClassifier_RobustScaler.ipynb |
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# # Counting Sort
# ### Constraints:
# - There are No... | Algorithms/SearchingAndSorting/Counting_Sort.ipynb |
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# + executionInfo={"elapsed": 2990, "status": "ok", "timestam... | EEG/model/STEW_autoKeras.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # P... | code/Python performance optimization.ipynb |
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import pandas as pd
import numpy as np
import matplo... | DataAnalytics/Analysis.ipynb |
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from utils import utils
from utils import scale_by_sca... | 3_Generate_data_on_a_grid.ipynb |
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# # A.1. Data Curation
# ## <NAME>
#
# The necessary i... | hcds-a1-data-curation.ipynb |
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# ## ... | 1_introduction.ipynb |
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# # Procedure
# There are many approaches... | notebooks/2_procedure.ipynb |
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import psycopg2
import psycopg2.extras
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# + colab={} colab_type="code" id="rDUdNeNd6xle"
# Imp... | 9_Validate_3D_CNN_whole_ds_wb_rawdat_mwp1_CAT12_MNI_ADNI3_amy.ipynb |
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# ## Devise
#
# What if we could get a set of word and... | live_notes/dl2_042_devise.ipynb |
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import numpy as np
import pandas as pd
... | Matplotlib Tutorial.ipynb |
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# + [markdown] slideshow={"slide_type": "s... | in-class-exerices/wk-05-logic-conditions.ipynb |
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# <a href="https://colab... | Tarea11.ipynb |
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# # Topic modelling on news data for 10 Topics
#
# - D... | Topic modeling on text data-10_Topic.ipynb |
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import time
import random
# creates an array of 10000... | Algorithms/Sorting.ipynb |
# ## Manipulating data
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# %matplotlib inline
data = pd.read_csv('data/nyc_data.csv', parse_dates=['pickup_datetime',
'dropoff_datetime'])
fare = pd.read_csv('data/nyc_fare.csv', parse_dates=['pick... | Section 2/22-manipulating.ipynb |
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# + [markdown] id="oXs... | notebooks/6-1.sigmoid_function.ipynb |
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# + _cell_guid="b1076dfc-b9ad-4769-8c92-a6c4dae69d19" ... | models/simple-nn-using-old-cv-markpeng.ipynb |
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import sqlite3
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# + [markdown] id="CwNLv6dKKny3"
# ## Interacting with... | examples/datastream_operation.ipynb |
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# <b> <font size =5> Calculate Distance from Each Faci... | Notebooks/Calculate-Distance-To-High-Facilities.ipynb |
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# #!/usr/bin/en... | train_commonfns.ipynb |
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#hide
# %load_ext autoreload
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# default_exp m... | 02_model.ipynb |
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# %% [markdown]
# # ... | 3. Natural Language Processing with Sequence Models/Week 2 Recurrent Neural Networks for Language Modeling/Lab_1_Hidden State Activation.ipynb |
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# # K-Nearest Neighbors Classification Demo
#
# K-near... | cuml/kneighbors_classifier_demo.ipynb |
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# # RedGrease Demos
#
# Quick demonstratio... | examples/Demo.ipynb |
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# +
import sys ; sys.path.append('../')
import torchdy... | hypersolver/density_estimation/train_ffjord.ipynb |
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# # `TensorFlow`/`Keras`
#
# [Keras](https://keras.io/... | notebooks/05c_machine_learning_keras.ipynb |
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# # Module 2.8 Dictionaries, Summarized
#
# ... | modules/module-02/module2-dictionaries.ipynb |
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# ### install & docs
pip install qgrid
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# solving... | qgrid_on_method/qgrid_on_method.ipynb |
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# + pycharm={"name": "#%%\n"}
import os
import numpy a... | notebooks/artificial_bias_experiments/noisy_prop_scores/scar/table/noisy_prop_scores_scar.ipynb |
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### This is supposed to be a demo for how t... | inference_demo.ipynb |
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# + [markdown] id="UKxnCTGBNAmz"
# ### Load and clean ... | notebooks/kmeans.ipynb |
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# <img src="slide1.png" width="600" height="600">
# <... | Assignments/HW_3/Pandas_Titanic.ipynb |
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# This notebook was prepared by [<NAME>](http://donnem... | sorting_searching/selection_sort/selection_sort_challenge.ipynb |
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# + [markdown] application/vnd.databricks.v1+cell={"inputWidgets": {}, "nuid": "c469c9ee-3832-4f99-96ee-679bf24df825", "showTitle": false, "ti... | tutorials/Certification_Trainings/Healthcare/databricks_notebooks/6.Clinical_Context_Spell_Checker_v3.0.ipynb |
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# <img src="../../images/qiskit-heading.gif" alt="Note... | qiskit/basics/1_getting_started_with_qiskit.ipynb |
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# + id="T3tnX9Y7QmzK" colab_type="code" colab={}
"""Code based on R code, ava... | Monty_Hall/Monty_Hall.ipynb |
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# Write a program to identify sub list[1,1,5] is t... | day_5assignment.ipynb |
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# # Create a gene family network and Entrez Ge... | 2.families.ipynb |
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# # AWS STAC RTC
#
# Start exploring this ... | odc-stac.ipynb |
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# # Amazon Fine Food Reviews Analysis
#
#
# Data Sourc... | Support Vector Classification.ipynb |
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# + [markdown] colab_type="text" id="6uQP3ZbC8J5o"
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from os import path
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# # Regression diagnostics
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# License: BSD
# Author: <NAME>
from __future__ i... | transfer_learning_tutorial.ipynb |
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