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# # A brief analysis of QQ message
#
# There w... | Look Back 2017.ipynb |
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# # Color
#
# I can do no better than this blog post b... | fundamentals_2018.9/visualization/color.ipynb |
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# # 1-2.1 Intro Python
# ## Strings: input, testing, f... | Python Absolute Beginner/Module_1_2.1_Absolute_Beginner.ipynb |
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# ## Scrapes Google Play store website for apps using ... | play_store_scraper.ipynb |
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# # First Animation
# ---
#
# by <NAME>
#
# We draw a ... | BouncingBall_FirstAnimation.ipynb |
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import tensorflow as tf
tf.__version__
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mnist = tf... | Jupyter/mnist/.ipynb_checkpoints/Untitled-checkpoint.ipynb |
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# <div class="alert alert-block alert-info" style="mar... | Data Analysis with Python/Data Analysis with Python - Week 4 - Model Development.ipynb |
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#<NAME> - Programming with Data Project
#Predictio... | Grab_AI_for_SEA_Challenge_-_AL.ipynb |
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import sys
sys.path.append("..")
impo... | synthetic/zakharov.ipynb |
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import cv2 as cv
import numpy as np
img = cv.imre... | AI 이노베이션 스퀘어 시각지능 과정/202005/20200515/OpenCV smoothing & sharpening.ipynb |
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import numpy as np
import pandas as pd
df = pd.read_c... | Raquel/KaggleCompetition.ipynb |
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# ## `arcgis.mapping` module
# The `arcgis.mapping` mo... | guide/09-mapping-and-visualization/using-the-map-widget.ipynb |
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# # 文本情感分析
#
# 文本情感分析是NLP（自然语言处理）领域... | notebook/DL_text_sentiment_analysis/text_sentiment_analysis.ipynb |
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# # Objective
#
# Investigate ways to bound regions wi... | datasets/zoom_test/bound_crowded_regions_smfish_v2.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | module1/LS_DS10_231.ipynb |
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# # Demonstrate the "target-decoy" approach, as applie... | notebooks/DemonstratingTargetDecoyApproach.ipynb |
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# + [markdown] nbgrader={}
# # Codecademy Completion
... | assignments/assignment01/Codecademy.ipynb |
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# # Implementing Random Forest
# Authors:
# - <NAME>
... | AQI/models/5. Implementing Random Forest Classifier.ipynb |
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# # Trabajo Final Sistemas de Bases de Datos Masivos
#... | .ipynb_checkpoints/Trabajo Final Curso Grandes Bases de DAtos-checkpoint.ipynb |
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##Liberias
import pandas as pd
import numpy as np... | 3.Modeling/3.3.Clasifation_Random-Forest.ipynb |
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# # Velge kjerne
#
# ### Hva er en kjerne... | notebooks/Introduksjon til Dapla, JupyterLab og GitHub/Velge kjerne.ipynb |
# -*- coding: utf-8 -*-
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# # Classification
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in... | soln-julia/chap12.ipynb |
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# + [markdown] id="chEt2JOIePz0"
# ## 0. Preparation
#
# You have to move the... | scripts/2.Scraping/Twitter_API_demo.ipynb |
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import glob
import sys
sys.path.append(... | antigen_discovery/PredictionCollection.ipynb |
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# + id="k55zrcV_LTwc" colab_type="code" colab={}
import tensorflow as tf
from... | module-6/data/example1.ipynb |
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import numpy as np
import pandas as pd
import matplot... | malaria.ipynb |
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import os
import cPickle as pickle
from gensim.mo... | gensim/Untitled.ipynb |
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# ## Nuclear Morphology and Chromatin Organization Fea... | notes_on_feature_extraction/Nuclear_Features.ipynb |
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# <i>Copyright (c) Microsoft Corporation. All rights res... | scenarios/similarity/02_state_of_the_art.ipynb |
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# + [markdown] colab_type="text" id="cPKvKMkAkRMn"
# #... | site/en/guide/keras/custom_layers_and_models.ipynb |
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# ### Power On the Compute Server
import ... | Compute_Server/iDRAC.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as ... | visualization_stuff/visualise_boston.ipynb |
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# # Numpy Array Operations
#
# * Topicos:
# * Oper... | scripts_numpy_pandas/Numpy_03_operations.ipynb |
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import os, sys, gc
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import ... | phase1_scripts/inference_test9_epoch9.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | Copy_of_C4W4_Assignment.ipynb |
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# ## Python Movie Recommendation System
... | Projects/project-4-python-movie-recommendation-system.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Midterm_Num1.ipynb |
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import numpy as np
import matplotlib.pyplot as plt... | math/regression-linear.ipynb |
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# ## 2020년 3월 22일 일요일
# ### HackerRank - Hash Table : ... | DAY 001 ~ 100/DAY045_[HackerRank] Hash Tables Ransom Note (Python).ipynb |
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# # The Prevalence of Concussion in Amateur Irish Rugb... | Real World Data.ipynb |
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impo... | svm.ipynb |
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#library(tidyverse)
library(ggplot2)
#library(dplyr)
#regrex1 <- re... | Rscript1.ipynb |
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-- # Demo Notebook for "Automatic Differe... | notebooks/demo.ipynb |
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import loader
from sympy import *
init_printing()
from... | notebooks/vibration.ipynb |
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#
# Lambda School Data Science
#
# *Unit 2, Sprint 3, ... | module1-define-ml-problems/LS_DS_231.ipynb |
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# # Introduction
# This is an introductory tutorial to... | notebooks/archive/tutorial_esm4.ipynb |
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# # Principle component analysis for dimensional reduc... | simplePCAwithvisualization.ipynb |
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# ## scikit-learn中的多项式回归和Pipeline
import numpy as np ... | 08-Polynomial-Regression-and-Model-Generalization/02-Polynomial-Regression-in-scikit-learn/02-Polynomial-Regression-in-scikit-learn.ipynb |
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import pygame
from pygame.locals i... | RLGL.ipynb |
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import mhcflurry
import numpy
import se... | examples/class1_allele_specific_models.ipynb |
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# + id="mhfyHiq8wkNT" colab_type="code" colab={}
import tensorflow_datasets a... | tensorflow/text/transformer_model.ipynb |
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# https://leetcode.com/problems/find-the-differ... | lt_389_find_difference.ipynb |
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# + [markdown] id="NT4f2Kygv7iE"
# # Importation
# + ... | src/main/only_bounding_box_model/vgg-bounding-box-modified.ipynb |
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import os, glob, re, json, random
from tqdm.notebook i... | convert_to_dd_format.ipynb |
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instroom2016_2019 <- read.table("1e_asielaanvraag_instroom_2016_2019.csv... | InstroomAA1e_2016_2019.ipynb |
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# # Isostatic deflection in 2D
# Source: Hodgetts et ... | IsostaticDeflection/IsostaticDeflection.ipynb |
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import numpy as np
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# # MODNet 'matbench_phonons' be... | matbench_phonons/phonons_benchmark.ipynb |
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a = [1,2,3,4,5,6]
a.index(1)
a.index(2)
# ## 言论过滤
#... | SupervisedLearning/04. NaiveBayes/SpamClassification_NaiveBayes.ipynb |
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# # Create metadata
#
# This notebook crea... | csv-on-the-web-working-with-energyplus-results/create_metadata.ipynb |
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# +
# con_contact
# Authors: <NAME>, <NAME>
# Example ... | examples/con_contact.ipynb |
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# + slideshow={"slide_type": "notes"}
from IPython.cor... | Lecture 4, Steepest descent and Newton's method for unrestricted optimization.ipynb |
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# # Regression and Other Stories: Sex Ratio
import ar... | ROS/SexRatio/sexratio.ipynb |
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import numpy as np
import pandas as p... | NN_AuthorshipID/data_helpers.ipynb |
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# + [markdown] deletable=false
# # [Applied Statistic... | _as/2019/jp/06.ipynb |
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# <a href="https://colab.research.google.com/github/DingLi23/s2search/blob/pi... | pipelining/pdp-exp1/pdp-exp1_cslg-rand-500_plotting.ipynb |
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import numpy
ar1=numpy.array([2,4,5,6,7])
ar2=numpy.ar... | ML/ML_Practice.ipynb |
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# ### Your Turn! (Solution)
#
# In the last video, you... | 03_unsupervised_learning/4_PCA/.ipynb_checkpoints/Interpret_PCA_Results_Solution-checkpoint.ipynb |
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# # Getting started with Python for Data Science and A... | GETTING-STARTED.ipynb |
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# + [markdown] graffitiCellId="id_18ngdm1"
# # Linked ... | practice/linked_lists/3_linked_list_practice.ipynb |
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# + run_control={"frozen": false, "read_only": false}
... | 4-Copy1.4.4 Unsupervised Neural Networks and NLP.ipynb |
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# <b>Calcule a integral dada</b>
# $\int \frac{x}{\sq... | Problemas 6.1/14.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | prediction/single task/code comment generation/t5 interface/java_base_model.ipynb |
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# + [markdown] id="a5EkLOFwB0Nx"
# #Anomaly Detection with Adaptive Fourier F... | Paper Experiments/Anomaly_Detection_AdaptiveFF_Real_Quantum_Computer.ipynb |
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# #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
@autho... | hw2.ipynb |
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# <a href="https://colab... | code/Interactive_Plotting_With_Bokeh_First_Steps.ipynb |
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# + [markdown] colab_type="text" id="iCUZvZvBB7VD" sli... | tensorflow_probability/examples/jupyter_notebooks/Linear_Mixed_Effects_Models.ipynb |
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from sklearn.cl... | examples/example1.ipynb |
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# + _uuid="8f2839f25d086af736a60e9eeb907d3b93b6e0e5" _... | kernel11745e1115.ipynb |
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# # Optimisation
# https://docs.scipy.org/doc/scipy/re... | notebooks/Optimisation.ipynb |
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# # Spark + Kafka
#
# ```{note}
# Structured Streaming... | stream/4.kafka.ipynb |
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# # Max-min fairness
# https://www.wikiwand.c... | algorithms/Max-min-fairness.ipynb |
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# + [markdown] colab_type="text" id="ewbWLGf0hYbt"
# #... | demos/PCT5300-Reese-CoraClassification/python/part_3_feature_importance.ipynb |
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# # Линейная регрессия и основные библиотеки Python дл... | 2. Supervised Learning/Linear Regression/weight_height/linRegression.ipynb |
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# # Simple Linear... | Python_Stock/Basic_Machine_Learning_Predicts.ipynb |
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imp... | book/Chapter 20 - Performance Visualization/Combined Models.ipynb |
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# <style>
# .nbinput .prompt,
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# + [markdown] id="Y4YlT-8B8lLN"
# # SMI AL Loop
# + ... | benchmark_notebooks/similar/redundancy/Similar_Redundancy.ipynb |
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# # Visualizing Hidden Layers
# +
# %matplotlib noteb... | solutions_do_not_open/Lab_12_DL Visualizing Hidden Layers_solution.ipynb |
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# The notebook gives the experiment reported in Fig. 4... | lin_reg/LinearReg_with_Gaussian_noise.ipynb |
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"""
18. How to convert the first character of each element in a series to uppercase?
"""
"""
Difficulty Level: L2
"""
"""
Change the first character of each word to upper case in each word of ser.
"""
"""
ser = pd.Series(['how', 'to', 'kick', 'ass?'])
"""
# Input
ser = pd.Series(['how', 'to', 'kick', 'ass?'])
# S... | pset_pandas_ext/101problems/solutions/nb/p18.ipynb |
# -*- coding: utf-8 -*-
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# # Deutsch-Jozsa algorithm
#
# The ... | DeutschJozsaAlgorithm/DeutschJozsaAlgorithm.ipynb |
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# # Problemy wydawania reszty i problem plecakowy
#
# ... | problem plecakowy/Problem wydawania reszty i problem plecakowy.ipynb |
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# # DataPath :: Data Update Example
# This notebook de... | docs/derivapy-datapath-update.ipynb |
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# # Initial enthalpy calculations and enthalpy modelli... | docs/examples/initial_enthalpy.ipynb |
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# ## Testing Distributions
#
# As the start of our sec... | code/testing_distributions.ipynb |
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from collections import Counter
import json
impor... | validation_predictions.ipynb |
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# Import Python libraries
from typing import *
imp... | tutorials/market/Market_Intelligence_Part2.ipynb |
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import matplotlib.pyplot as plt
# %... | visualize_target_prediction.ipynb |