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class Solution:
def convertToTitle(self, n: in... | Math/1225/168. Excel Sheet Column Title.ipynb |
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# # Fake news detection
# A fake news are those stori... | FakeNewsDetection.ipynb |
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# # Steam reforming with water-gas shift
#
# ## Known ... | DR_WGS.ipynb |
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# The following example shows you how to display the d... | src/notebooks/184-lollipop-plot-with-2-groups.ipynb |
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# + [markdown] tags=[]
# # Example: CanvasXpress meter... | tutorials/notebook/cx_site_chart_examples/meter_5.ipynb |
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from IPython.display import HTML
# Cell visibilit... | ICCT_si/examples/01/.ipynb_checkpoints/M-08_FFT-checkpoint.ipynb |
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# ## RF
# import xgboost as xgb
from sklearn.ensemble... | orig_files/14_xgboost.ipynb |
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pip install psycopg2-binary
pip install pprint
impor... | module4-acid-and-database-scalability-tradeoffs/Julie_DS324_PostgreSQL_Titanic.ipynb |
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# # Procesamiento de los datos
#
# Limpieza y transfor... | data_processing.ipynb |
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import os
import logging
from io import BytesIO
im... | modeling/Sequence/Sequence.ipynb |
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# name: python385jvsc74a57bd016e3f6170213bc8b93f4af10cda404198c09c84502cee13f546aa00fc3fa... | python_bas.ipynb |
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# ## 1. Import MNIST data
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from tensorflow.example... | Lab9/TF_DNN_example.ipynb |
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def train_LSTM(model, input_, target, epochs = 100, op... | cs224w/one3.ipynb |
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# # Importing libraries and Dataset
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import pandas... | Assignment 1/Healthcare.ipynb |
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import matplotlib.pyplot as plt
import tensorflow as t... | 3(Training). Naval Mine Identifier (Multilayer Perceptron) NN Tensorflow .ipynb |
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# ## Programming exercises##
#
# +
#1.Write a program... | Problems.ipynb |
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# # BLU03 - Learning Notebook - Part 3 of 3 - Web scra... | S02 - Data Wrangling/BLU03 - Data Sources/Learning Notebook - Part 3 of 3 - Web scraping.ipynb |
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# Rossman store sales example
# data from https://ww... | predict-sales/predict-store-sales.ipynb |
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# # Predicting Student Admissions with Neural ... | intro-neural-networks/student-admissions/StudentAdmissions.ipynb |
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import nltk
nltk.download('all-corpora')
nltk.dow... | 1.NLP_PREP/1.3.1.1.nltk.ipynb |
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# # Programming_Assingment13
# ### Question 1:
# ... | Programming_Assingment13.ipynb |
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# # Overview of `eolearn.core`
#
# `eolearn.core` is t... | examples/core/CoreOverview.ipynb |
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import subprocess
import os
import pandas as pd
i... | notebooks/step1_Data understanding.ipynb |
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# # Question and Answer
import logging
import json
fr... | Transformers/Tasks/question-answering-simple-training.ipynb |
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# # ElasticNet Regression with scikit-learn
# This no... | code/day_5/7 - ElasticNet Regression with Sklearn.ipynb |
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# # AWS Elastic Kubernetes Service (EKS) Deep MNIST
# ... | examples/models/aws_eks_deep_mnist/aws_eks_deep_mnist.ipynb |
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# + colab={"base_uri": "https://localhost:8080/", "hei... | mirimages-master/06_SimpleDL_MultiTask_Valid.ipynb |
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# # KMeans Clustering Example
# A data set that ident... | Python-API/pal/notebooks/irisFlowerClustering.ipynb |
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# + [markdown] colab_type="text" id="77gENRVX40S7"
# ##### Copyright 2019 The... | site/en/tutorials/images/transfer_learning.ipynb |
# -*- coding: utf-8 -*-
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from model import *
from data import *
# ## Train yo... | trainUnet.ipynb |
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# # Sistemas Inteligentes
#
# ## Exercício Computacion... | limitadas/sistemas-inteligentes/RICARDO SUYAMA com LUNEQUE JUNIOR e TITO CACO/q3-2018/ec5/.ipynb_checkpoints/EC_5-checkpoint.ipynb |
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# %matplotlib inline
import math
import numpy as np
im... | pyglidein world plot.ipynb |
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# <a href="https://colab.research.go... | t81_558_class_01_5_python_functional.ipynb |
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# # Feature Engineering
# * **Description**: COMP4103... | feature_engineering.ipynb |
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#API request to get data
import requests as req
url = ... | jupyternotebook/RecommendationUsingKNN.ipynb |
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import operator
import math
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import os
path = os.path.join('/home/santiago/Document... | examples/simulation/Build Simulation Model.ipynb |
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import matplotlib.py... | 5_dft_properties.ipynb |
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# ## 0.1 Course overview
# ### 0.1.1 Course character... | Course 1_Probability - The Science of Uncertainty and Data/Unit 0 Overview.ipynb |
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# ## Nested clustering of cells in the HLCA, and clust... | notebooks/1_building_and_annotating_the_atlas_core/06_nested_clustering_and_cluster_DEA.ipynb |
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# # Lists in Python
#
# <p>
# In most languages a coll... | Notebooks/Example-004-Python-Lists.ipynb |
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# Copyright (c) Microsoft Corporation.<br>
# Licensed ... | machine-learning-notebooks/transfer-learning-custom-azureml/2.Upload_and_Label_with_AzureML.ipynb |
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# # Udacity DEND Project-3: AWS Set-up
# ### IaC set-u... | Udacity-DEND-Project-3-AWS-Setup.ipynb |
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# default_exp datasets.CombinedGenoPheno
# -
# # ... | 05_datasets_CombinedGenoPheno.ipynb |
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# # Mario corpus stats
#
# Stats computed on Super Mar... | notebooks/mario_corpus_stats.ipynb |
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# Testing Notebook
import pandas as pd
import numpy a... | test_notebook.ipynb |
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# Most examples work across multiple plotting backends, this example is also available for:
#
# * [Matplotlib area_chart](../matplotlib/area_c... | examples/gallery/demos/bokeh/area_chart.ipynb |
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# + id="PgDXXup9-RSG"
import numpy as np
# + [markdown] id="rytLawcv9Hpo"
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# ### Find duplicate samples
# The bits of interactive... | notebooks/rawdata_verification.ipynb |
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# %load_ext Cython
# # Twitter Sentiment
# ##### <NAM... | TwitterSentiment.ipynb |
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# #Fire up graphlab create
import graphlab
# #Load s... | Studying Materials/Course 1 ML Foundations/Regression/Predicting house prices.ipynb |
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# # TDA with Python using the Gudhi Library
#
# # Re... | Tuto-GUDHI-cubical-complexes.ipynb |
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# import necessary packages
import os
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# ## Playing with PUDL
# This notebook is meant to hel... | results/notebooks/eia923/fuel_receipts/EIA923_fuel_exploration.ipynb |
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# + [markdown] id="mKUSMFVqINo-"
# ## Preprocessing
#... | Deep_Learning.ipynb |
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# # DAY 2-1ST PYTHON ASSIGNMENT
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#Question 1
#Try ... | DAY2/Assignment Day 2.ipynb |
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# import libraries
import folium
import pandas as ... | TRABAJO ANALITICA/Untitled.ipynb |
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# %load_ex... | testing-exercises.ipynb |
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# # Ploting different new features
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import numpy a... | dev/test.ipynb |
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# # N-Year Thresholds
# The N-Year thresholds, which a... | n-year/notebooks/N-Year Thresholds.ipynb |
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# + [markdown] nbsphinx="hidden"
# # Random Signals an... | random_signals_LTI_systems/correlation_functions.ipynb |
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# + colab={"base_uri": "https://localhost:8080/", "height": 203} id="4i71CtFk... | Day-28/Sentiment_Analysis.ipynb |
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import os
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import tempfile
import url... | iris_example.ipynb |
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# # Tools scripts
# The notebook must run in the same ... | sub_cut.ipynb |
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# In this notebook, we com... | examples/Controlled_Invariant_Sets/Planar_System_bounded_univariate_control.ipynb |
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# # Jupyter notebook example
# This is an example Jup... | jupyter-notebooks/jupyter_notebook-basic.ipynb |
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# ## Preprocessing
# + colab={"base_uri": "https://localhost:80... | src/finalModels/AdaBoost/Adaboost_NoWE.ipynb |
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import pickle
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def load_data():
... | Lectures/search_in_practice-approximate_nearest_neighbors/Trees and Forrests.ipynb |
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# https://machinelearningmastery.com/check-point-deep-... | keras/180102-checkpoint.ipynb |
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# # How to size your bets - The Kelly Rule
# he Kelly... | 05_strategy_evaluation/05_kelly_rule.ipynb |
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# + colab={} colab_type="code" id="ur8xi4C7S06n"
# Cop... | tables/automl/notebooks/purchase_prediction/purchase_prediction.ipynb |
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from datetime import datetime
import mxnet as mx
f... | exam.ipynb |
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# # Helpdesk Hard
import getpass
import psycopg2
from... | Python/12-3 Helpdesk - Hard.ipynb |
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# ## Plot survival prediction... | 06_predict_survival/plot_survival_results.ipynb |
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# Pandas library for the pandas dataframes
import ... | final_jupyter_notes/svm_rbf_final.ipynb |
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import pandas as pd
fraud_df = pd.read_csv("Finan... | Chapter06/Credit Card Fraud Detection/Credit Card Fraud Detection.ipynb |
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# %matplotlib inline
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# + id="ktFt6IzKJkSn" colab_type="code" colab={}
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# + id=... | Chapter15/Activity15.01/Activity_15_01_Benchmark_Model_using_Logistic_Regression_v1_0.ipynb |
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# + [markdown] id="AYV_dMVDxyc2"
# [` method in pandas
#
# Sometimes... | reference/Using the apply method in pandas.ipynb |
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# + [markdown] slideshow={"slide_type": "s... | docs/notebooks/PrototypingWithPython.ipynb |
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# ## **Следующий раздел посвещен векторизации рабочего... | jupyter_notebooks/fit_randomizer.ipynb |
# -*- coding: utf-8 -*-
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# ## Errores estándar
#
# Hemos mostrado cómo en... | linear/standard_errors_R.ipynb |
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# ## Runtime
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... | Sensitivity-Analyses-of-Exoplanet-Occurrence-Rates-from-Kepler-and-Gaia/occurrence_rate_plotting_Figure_1.ipynb |
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# # Analyzing OpenFOAM Data in Python
# #... | Paper2_OptimizingRestoration/Notebooks/Analyzing_OpenFOAM_with_Python.ipynb |
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im... | lessons/regression-lesson.ipynb |