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# **input - print**
name = input("enter a name: ")
pr... | session-2/notebook_2.ipynb |
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# + id="s4x2sL4askdI"
# + [markdown] id="_aOcipcj3bdH"
# # 5. Automatic Dif... | 03 Calculus for ML (Jon Krohn)/CALC I 05 Automatic Differentiation.ipynb |
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# # Assignment 2 | Programming Logic
#
# Reminder: in ... | assignments/assignment_2/assignment_2_JulianaRO.ipynb |
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import matplotlib.pyplot as plt
import numpy as np... | MIDOSS/Snowflake.ipynb |
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# Think Bayes
# -----------
#
# Example problem relate... | examples/voter.ipynb |
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# # Creating a Sentiment Analysis W... | project-deployment/SageMaker Project.ipynb |
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# # Image Captioning with RNNs
# In this exercise you ... | assignment3/.ipynb_checkpoints/RNN_Captioning-checkpoint.ipynb |
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#url = https://opendata.cwb.gov.tw/fileapi/v1/open... | Untitled.ipynb |
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# Observed and Projected Climate Shifts http://koeppen... | .ipynb_checkpoints/cli.011_New -checkpoint.ipynb |
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# # Lab 1: Tools of the trade
#
# ## Goal:
# At what r... | lab1/lab1-HOWARD.ipynb |
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# Monte Carlo integration is a t... | integration/homework.ipynb |
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# + [markdown] colab_type="text" id="0TD5ZrvEMbhZ"
# #... | tensorflow/contrib/eager/python/examples/generative_examples/cvae.ipynb |
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# <html>
# <body>
# <table style="border: none" al... | applied-ai-apach-system-ml-and-dl4j/WML/a3_m4_WML_TF_Train_Save_Model_publish.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | probability and stats/ipl.ipynb |
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# ---... | notebooks/crop_dataset.ipynb |
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# # Basis Sets
# + run_control={"frozen": false, "re... | Tutorials/01_Psi4NumPy-Basics/1g_basis-sets.ipynb |
#!/usr/bin/env python
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# # ATLAS Test Beam Data
#
# Pyt... | AppStat2022/Week6/original/ATLAStestbeam/ATLAStestbeam.ipynb |
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import pandas as pd
import numpy as np
#import xlrd
im... | doc/.ipynb_checkpoints/AFM_loaddata-checkpoint.ipynb |
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import seaborn as sns
import matpl... | analysis/result_analysis-3-iter.ipynb |
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# %run setup.py
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from exoplanet.utils import eval_... | paper/notebooks/(5.1) SNR vs asini relations.ipynb |
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# <a href="https://colab... | PythonProgramming.ipynb |
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# + _cell_guid="b1076dfc-b9ad-4769-8c92-a6c4dae69d19" ... | DS201/DS201DrugReviewsProj/DRUG_REVIEW_ML.ipynb |
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def move_glob(ds... | notebook/shutil_move_glob.ipynb |
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# +... | Bidirectional LSTM.ipynb |
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# # Web Scraping Dynamic Javascript Web Page
# ## Env... | dynamic-web/dynamic-JS-scraping-with-selenium.ipynb |
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# # 4. Custom Model
# This guide will step through the... | docs/4. Custom Model.ipynb |
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# # Exponential, Log
#
# 1. np.exp() : $e^{x}$
# 2. n... | 1.Study/2. with computer/4.Programming/2.Python/9. Numpy/ch3/Chapter3 Mathematical Functions_Notebook3 Exponents and Logarithms.ipynb |
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import pickle, os, torch
import os.path as... | analysis/GNN_plots_all_corr.ipynb |
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# # Курс «Алгоритмы анализа данных»
# ## Урок 6. Град... | Lesson 6.ipynb |
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from matplotlib import ... | notebooks/comparison_experiment_difference_cellSample_Minus_cell_correct_and_withCOLL_manipulatre.ipynb |
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# Paper explaining CenterNet: [Objects as Points](http... | notebooks/references.ipynb |
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# <h1 id="tocheading">Contents</h1>
# <div id="toc"></... | Lesson12.ipynb |
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from IPython.core.display import display, HTML
display... | notebooks/mouse_brain/broad_population/scGeneFit_without_filtering.ipynb |
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# + id="RDjai3DUXAFs"
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import os
from IPython.display import Image... | cnn/result.ipynb |
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# + [markdown] colab_type="text" id="Za8-Nr5k11fh"
# ##### Copyright 2018 The... | courses/udacity_intro_to_tensorflow_for_deep_learning/l01c01_introduction_to_colab_and_python.ipynb |
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from IPython.display import Video
Video('test_run/pya... | Untitled.ipynb |
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# + [markdown] id="Xdl-8Vu0ve0n"
# # I. Gene Expression Features Correlation ... | 4.Gene Expression Prediction.ipynb |
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#pip install git+https:/... | backtesting.ipynb |
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# ## NLP (Natural Language Processing) with Python
#
#... | News-Classifier.ipynb |
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import numpy as np
import scipy.stats as stats
import ... | HW2/HW2.ipynb |
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# # <span style="color:orange">Anomaly Detection Tuto... | tutorials/Anomaly Detection Tutorial Level Intermediate - ANO102.ipynb |
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# # 데이터 불러오기
# +
import pandas as pd
df = pd.read_cs... | .ipynb_checkpoints/20201024_data_analysis_with_covid19-checkpoint.ipynb |
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# # Candy Trade
# This notebook contains all data and ... | candy_trade.ipynb |
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# + [markdown] colab_type="text"
# # Convolutional aut... | examples/vision/ipynb/autoencoder.ipynb |
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# ### Importing the Libraries
# At first, we will loa... | 01_data_clean.ipynb |
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import numpy as np
# # Salads
# ... | SALAD/SLD_CONCATENATE_DATAFRAMES.ipynb |
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# # OPICS Multiprocessing
#
# OPICS suppo... | docs/source/notebooks/03-Multiprocessing.ipynb |
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# 1. Iterate over a list
import pandas as pd
car_mode... | Chapter01/.ipynb_checkpoints/Exercise 1.03-checkpoint.ipynb |
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import pandas as pd
import json
import... | analysis/tl_2v2/summary.ipynb |
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import spacy
nlp = spacy.load("en_core_web_lg", exclu... | notebooks/literature_review-examples.ipynb |
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# + [markdown] id="zMkw96ZTKbFi" colab_type="text"
# # POETRY GENERATION USIN... | poetry_generator/poetry_generator.ipynb |
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# # Demand Learning Comparison
#
# This notebook runs ... | demand_learning.ipynb |
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# # Forecasting
import panda... | labs/lab7/forecasting.ipynb |
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# <dl class="dl-horizontal">
# <dt>Title</dt> <dd> Text Element</dd>
#... | examples/reference/elements/matplotlib/Text.ipynb |
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# <small><small><i>
# All the IPython Notebooks in thi... | 002_Python_Functions_Built_in/019_Python_staticmethod().ipynb |
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import pandas as pd
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# # 04. Convolutional Neural Network(CNN)으로 숫자 분류기 구현하... | Lecture_Note/03. CNN Application/04.cnn_mnist.ipynb |
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my_list
my_list=['a',1,2.3]
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# # Cyber Use Case Tutorial #2: Network Mapping using ... | blog_notebooks/cyber/network_mapping/lanl_network_mapping_using_rapids.ipynb |
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import numpy as np
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# Dataset Source : Kaggle Dataset
#
# Resource and Cod... | DogeCoin/DogeCoin Price Prediction.ipynb |
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# %matplotlib inline
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import pandas as pd
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# + [markdown] papermill={"duration": 0.015866, "end_t... | trend_following_baltas2020.ipynb |
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# + [markdown] origin_pos=0
# # 自动并行
# :label:`sec_auto_para`
#
# 深度学习框架（例如，MxNet和PyTorch）会在后端自动构建计算图。利用计算图，系统可以了解所有依赖关系，并且可以选择性地并行执行多个不相互依赖的任... | submodules/resource/d2l-zh/mxnet/chapter_computational-performance/auto-parallelism.ipynb |
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# # Performance programming
# We've spent... | module09_programming_for_speed/09_00_performance_programming.ipynb |
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import sisl
impo... | ts-tbt-sisl-tutorial-master/TB_03/run.ipynb |
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# #### Installation of R packages
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#install.packages("ISwR")
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# + [markdown] id="view-in-github" colab_type="text"
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# # Predicting categories with Logistic Regression
#
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# Datos son como el petroleo
# Sugerencias de personas... | Theory/Ejemplos de data science.ipynb |
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# HIDDEN
from datascience import *
from pro... | notebooks/Chapter_06/00_Random_Counts.ipynb |
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# from swaptest import cswaptest
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# + [markdown] id="view-in-github" colab_type="text"
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# ## Inflected verbs
#
# #### Set-up and initializatio... | binder/11 Regenerate inflected verbs.ipynb |
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# In histograms, x axis contains a variabl... | 03_DataVisualization/05_HistogramPlots.ipynb |
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# # Dummy Variables Exercise
#
# In this exercise, you... | ETL/Solutions/12_dummyvariables_exercise-solution.ipynb |
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import tensorflow as tf
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# # Li-Li Cycle Test Plots
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# # Express sklearn pipeline as codeflare pipeline
#
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# + [markdown] nbsphinx="hidden"
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# + [markdown] id="Euiq_EOntgQm" colab_type="text"
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# ## Basic KB-NUFFT Example
#
# This notebook implemen... | notebooks/basic_examples_tf.ipynb |
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# # Anchor explanations for fashion MNIST
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# ### Note
# * In... | Resources/PyCitySchools_starter.ipynb |
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