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# # Ch4.1 Simple Scatter Plots
# %matplotlib inline
i... | III_DataEngineer_BDSE10/1905_Python/TeacherCode/datascience/Ch4.1_Simple_Scatter_Plots.ipynb |
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import sys
import os
import phys
phys.Measurement... | examples/code_unit_scale_test.ipynb |
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# Quickstart
# ==========
#
# In this short tutorial w... | tutorials/Quickstart.ipynb |
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# # Load data, train model
import numpy as np
import ... | notebooks/brca.ipynb |
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# # UNCLASSIFIED
#
# Transcribed from FOIA Doc ID: 668... | Module - Regular Expressions.ipynb |
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import pandas as pd
import nltk
import re
nltk.downlo... | fakeNewsDetection.ipynb |
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# # 1. Introduction to Python & Notebooks
# <datahub ... | econ-135-s2022-ps01.ipynb |
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from arcgis.gis import GIS
gis = GIS("https://www.arc... | Chapter_12/Add Data to Map.ipynb |
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# ### Comparison of Data Engineering Techniques
from ... | Comparison of pipelines.ipynb |
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#Problem 1
#Create a generator that generates the... | Section9.3 Iterators and Generators Homework.ipynb |
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#
# Working through the example from
# https://git... | kipet_examples/.ipynb_checkpoints/Ex7_concentration_input_wk.py-checkpoint.ipynb |
# -*- coding: utf-8 -*-
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# ## Spatio-temporal functional data analysis fo... | Spatio-temporal FDA/code.ipynb |
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# ## Start the 3D Visualizer and the droid... | examples_and_tutorials/notebooks/hello-robot-droidlet-intro.ipynb |
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# -*- coding: utf-8 -*-
from __future__ import uni... | cnn/word_accetuation/cnn_dictionary/v1_4/character_based_ffnn_keras.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as p... | cnn/compare_models/compare.ipynb |
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# # 模型训练过程分析
#
# ## 引入第三方包
# +
import glob
import pic... | notebook-examples/chapter-6/4_trainning_analysis.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | MACD_RSI_STOCHASTIC_strategy_(ccxt).ipynb |
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# + [markdown] nbgrader={}
# # Integration Exercise 2
... | assignments/assignment09/IntegrationEx02.ipynb |
# -*- coding: utf-8 -*-
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# -... | Tutorials/09_Configuration_Interaction/9a_cis.ipynb |
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# -----------... | notebooks/network-spatial-autocorrelation.ipynb |
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import pickle as p
import numpy as np
import tenso... | 6.S191-Lab1.ipynb |
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# Import required modules
from urllib.request import u... | NFL_team_stats.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | LeNet/7_1_MNIST_with_LeNet.ipynb |
; -*- coding: utf-8 -*-
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; ## GDL ... | tests/notebooks/ipynb_idl/demo_gdl_fbp.ipynb |
# # 📝 Exercise 02
#
# The aim of this exercise is to find out whether a decision tree
# model is able to extrapolate.
#
# By extrapolation, we refer to values predicted by a model outside of the
# range of feature values seen during the training.
#
# We will first load the regression data.
# +
import pandas as pd
pe... | notebooks/trees_ex_02.ipynb |
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# # Feature importance analysis
# for Tree Mortality P... | TreeMortalityPrediction_FeatImpAnalysis.ipynb |
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# Import libraries
import pandas as pd
# ### Scrape 2... | group_files/jane/notebooks/salary_scrape_pandas.ipynb |
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# + [markdown] id="0rmnHFFLAbuK"
# <font size = "5"> *... | Introduction/TestNotebook.ipynb |
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# # 0.0 Importar pacotes
from matplotlib import grids... | Projeto-Insight.ipynb |
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import pandas as pd
import numpy as np
import time... | P3-Kaggle-Clasificacion/P3/.ipynb_checkpoints/prueba19Final-checkpoint.ipynb |
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# cd /Users/martin/Git/estates
import os
import boto3... | notebooks/01_dynamodb.ipynb |
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# # Comparison star generator
# ## For information ab... | stellarphot/notebooks/comp-stars-template.ipynb |
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# name: python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east... | mlops-template-gitlab/seedcode/mlops-gitlab-project-seedcode-model-build/sagemaker-pipelines-project.ipynb |
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# # Animations with Adampy
#
# By creating animations ... | notebooks/phiweek-2019/4. Animation.ipynb |
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# + [markdown] extensions={"jupyter_dashboards": {"ver... | samples/02_power_users_developers/population_exploration_dashboard.ipynb |
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# + [markdown] id="WoAJAn5SAkY0" colab_type="text"
# #... | FeatureEngineering_DataScience/Demo181_RareCategories_SomeCategories.ipynb |
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import numpy as np
import os
import matplotlib.pyp... | plot_Fig12_nsat.ipynb |
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# Use numpy to convert to arrays
import numpy as np
i... | examples/regression_methods/RandomForest_Regression.ipynb |
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# %load_ext autoreload
# %autoreload 2
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import... | notebooks/60_swivel_tune.ipynb |
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import requests
# ## Function builder
dictToSend = {... | backend/backend_test.ipynb |
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# name: python383jvsc74a57bd0aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b7... | ENA2019/04BDatabaseModelWithTransportVariables.ipynb |
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# # 4.1. Evaluating the time taken by a command in IPy... | chapter04_optimization/01_timeit.ipynb |
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# # Newton's Method for finding a root
#
#
# [Newton's... | day4/Newton-Method.ipynb |
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# Name: example_calibration_analysis.ipynb
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import cvxpy as cp
import numpy as np
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# # write errors to file (doesn't work in Jupyter, onl... | code/.ipynb_checkpoints/6_error_handling-checkpoint.ipynb |
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# + [markdown] colab_type="text" id="K4i5n883p_Xf"
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# # Beginner's Python: Session Two - Politics and Soci... | session-two/subject_questions/session_two_politics_exercises.ipynb |
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# + [markdown] deletable=true editable=true
# # Filter... | docs/notebooks/Filters Tutorial.ipynb |
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# ### Average Reward DQN
# \begin{eqnarray... | src/forest/main.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | module1-statistics-probability-and-inference/ASartan_LS_DS_132_Sampling_Confidence_Intervals_and_Hypothesis_Testing_Assignment.ipynb |
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# # Structural Reliability - Basics and Example
# This... | SimpleReliability.ipynb |
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# + id="dNPR9GYHcgU0" colab={"base_uri": "https://localhost:8080/"} execution... | Question_Scoring/BERTforSequenceClassification.ipynb |
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# # Mini Project: Sorting and Evaluating Math Expressi... | mp_calc/mp2_exercises.ipynb |
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# %pylab inline
from sympy import symbols
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# # Training AU visualization model
# You will first n... | notebooks/_build/html/_sources/content/dev_trainAUvisModel.ipynb |
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# # Amazon SageMaker を使用した $K$-means クラ... | introduction_to_amazon_algorithms/kmeans_news_clustering/kmeans_news_clustering_lowlevel.ipynb |
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# Google Colab Setup
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#
# Make sure to select GPU... | 02 Intro to Q-learning and DQN.ipynb |
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# # Deep Learning with Python
#
# ## 4.5 The universal... | ch4/4.5 The universal workflow of machine learning.ipynb |
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# ## This notebook handles mapping srprec to census tr... | .ipynb_checkpoints/27_combine_census_data-checkpoint.ipynb |
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# %matplotlib inline
#
# # Isotonic Regression
#
#
# ... | scikit-learn/plot_isotonic_regression.ipynb |
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# # Variational Autoencoder in TensorFlow
# The main ... | .ipynb_checkpoints/vae-checkpoint.ipynb |
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# # Modeling and Simulation in Python
#
# Case study.
... | code/kitten.ipynb |
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# version 1.0.1
# #![Spark Logo](http://spark-mooc.git... | cs1001x_lab2.ipynb |
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import os
import json
from pathlib import Path
NEMO_P... | prepare_conf/gather.ipynb |
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# + [markdown] colab_type="text" id="BJsrTjueHRPH"
# # Introduction to Descri... | opends4all-resources/opends4all-machine-learning/SUPERVISED-ML-NN-neural-nets-intermediate.ipynb |
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# # 06 Machine Learning
# Logistic regression and rand... | notebooks/06_ML_model_building_tuning.ipynb |
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# <h2> Test macierzy numpy 2D <h2>
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# # Introduction to Hadoop MapReduce on Palmetto
# Ru... | intro-to-hadoop-00.ipynb |
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# # Filtrado de grupos
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# ## Searching for bouts for a day of alsa recording
... | notebooks/searchbout_s_b1253_21-Copy1.ipynb |
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# + id="WLAHnf5g4aLw" colab_type="code" colab={"base_uri": "https://localhost... | matrix_one/day3.ipynb |
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nltk.download('punkt')
nltk.download('word... | Training_Chatbot.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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import torch.utils.data as data
impor... | Make Training Data.ipynb |
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import logging
import importlib
importlib.reload(l... | notebooks/toy-1d-2d-examples/MoonTwoInvNetsAgain.ipynb |
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imp... | Metadata_of_Kaggle_dataset.ipynb |
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# + id="dKHHWgRDH9O6"
# !pip install pyyaml==5.1
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TORCH_VERSION ... | Segmentacao de instancia - toras.ipynb |
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# # What are `TargetPixelFile` objects?
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# %matplotlib inline
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i... | .ipynb_checkpoints/FrameInsert_eculidean-checkpoint.ipynb |
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# <div align="right"><i><NAME><br>12 August 2019</i></... | ipynb/Electoral Votes.ipynb |
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# # Leak Location model
# ## Introduction
# This code... | LeakLocation.ipynb |
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# + [markdown] hide_input=true
# # Risk analysis
# -
... | Prototype Notebook/FabianThesis.ipynb |
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money=float(input())
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// ## Refining till success or error; <NAME>... | notes/2019-09-18-refine-till-success.ipynb |
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import numpy as np # linear algebra
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# + id="RAoPUnFDSLD1"
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# # DTM-based filtrations: demo
#
# <NAME>, https://ra... | Demo.ipynb |
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