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# # Adaptive integration
using Fundamental... | book/localapprox/demos/adapt-usage.ipynb |
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# + [markdown] pycharm={"name": "#%% md\n"}
# # User I... | User Interfaces.ipynb |
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import numpy as np
import copy
import os
import ti... | DiabeticRetnopathy.ipynb |
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# # Models
# #!pip install seaborn
# %matplotlib inli... | notebooks/olives-model.ipynb |
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# <i>Copyright (c) Microsoft Corporation. ... | benchmarks/movielens.ipynb |
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# # Raw Voltage Visualization
# <a id="plot"></a>
# #... | docs/simpl_instructions/_build/html/_sources/raw_voltage.ipynb |
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# # Api Manager Example
from onesaitplatform.apimanag... | python-client/examples/ApiManagerClient.ipynb |
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from utils import *
watcha_data = read_data('../revie... | model/watcha_corpus.ipynb |
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import matplotlib.pyplot as plt
import pandas as p... | Weather_Py.ipynb |
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# # A Recurrent Network Mechanism of Time Integration ... | OLD VERSIONS/A Network Mechanism of Perceptual Decision Time-Copy1.ipynb |
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import random
import svgwrite
from svgpathtools im... | generators/b-coin/generator.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Tuesday/math2.ipynb |
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import tensorflow as tf
import numpy as np
# +
def a... | Simple seq2seq/predict_next2next_char.ipynb |
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# + id="aibYvylFpXAZ"
import torch
import torch.nn as ... | detector/other_notebooks/adversary.ipynb |
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# # Building your own TensorF... | advanced_functionality/tensorflow_bring_your_own/tensorflow_bring_your_own.ipynb |
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# + id="s6q3p6nu8M1p" colab_type="code" colab={"base_uri": "https://localhost... | Paper_Implementation/GIF_heatmap.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Chapter_15_Keeping_Time,_Scheduling_Tasks,_and_Launching_Programs.ipynb |
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# Ler um arquivo de configuração e aplicar como filtro
config_file = '/mnt/sadatalakevcbr/config/Engemix/dualmining_taglist.csv'
# lê arq... | pyspark/pyspark_read_config_file.ipynb |
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# + [markdown] nbgrader={}
# # Project Euler: Problem ... | assignments/assignment01/ProjectEuler1.ipynb |
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import pandas as pd
from cortex import Cortex
impo... | notebooks/name_parse/build_member_profile.ipynb |
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import numpy as np
import xarray as xr
import m... | copy_akwilson/19792005Hist.ipynb |
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# # Goals
#
# ### 1. Estimating training time befo... | study_roadmaps/1_getting_started_roadmap/7_extra_features/2) Estimate training time.ipynb |
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def joker (x):
return x ** 2
print (joker(2))... | python01.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | C2 Statistics and Model Creation/SOLUTIONS/SOLUTION_Tech_Fun_C2_S3_Inferential_Statistics.ipynb |
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import pandas as pd
df = pd.read_csv("pokemon-from-ka... | Pandas - Frequency Count.ipynb |
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# # Biomedical flows
#
# +++
#
# ```{margin}
# 
# ```
#
... | _build/jupyter_execute/content/research/biomedical.ipynb |
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// <a name="top"></a><img src="images/chisel... | 3.2_interlude.ipynb |
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import pandas as pd
import numpy as np
import matp... | 02_griding_cycles_ds.ipynb |
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# ## ${\textbf{Libraries}}$
# +
import numpy as np
im... | 21 - Customer Analytics in Python/7_Descriptive Analyses by Segments/3_Purchase Analytics Descriptive Statistics: Homework/Purchase Analytics Descriptive Analysis 8.2 Homework Solution.ipynb |
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# + [markdown] id="F77yOqgkX8p4"
# <a href="h... | demo/MMPose_Tutorial.ipynb |
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# # 7.17 Sizing of Pump for Oil Pipelines
# Crude oil... | docs/Examples/Crane TP 410 Solved Problems/7.17 Sizing of Pump for Oil Pipelines.ipynb |
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# + colab={} colab_type="code" id="hUkBRdY8ndhZ"
from matp... | Font_Rec(DeepFont).ipynb |
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# Import all the necessary files!
import os
import zip... | Course2/Course_2_Week_3.ipynb |
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import pandas as pd
from sklearn.preprocessing import ... | ML_Intrusion_Detection.ipynb |
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# # I. Introduction
#
# ![Simulated Annealing]... | Simulated_Annealing Algorithm.ipynb |
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# # QUESTION 1
#
# Using a lambda expression, complete... | .ipynb_checkpoints/Lab3-checkpoint.ipynb |
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# + [markdown] Collapsed="false"
# <img src='./img/Log... | atmosphere/20210506_wekeo_webinar/21_Sentinel5P_TROPOMI_NO2_L2_load_browse.ipynb |
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# # Exam 2
# ## <NAME>
# ### Problem 1: Controls
# I... | Exam_2_answers_Andrea_Escolar.ipynb |
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# + [markdown] kernel="Python 3 (ipykernel)"
# ## 1D Convolution
... | Catalogo2_Hernandez_Brenes_Porras/Convolution, spatial domain filters and low pass frequency domain filters/MetodosPythonCatalogo2.ipynb |
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# <img src="logo_img/logo.png" height=50 width=50 alig... | Analysis&Predictive Modelling of Proj.ipynb |
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import pandas as pd
import numpy as np
import matp... | self_organized_maps/som_icd_food_control_data.ipynb |
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import os
os.environ['CUDA_VISIBLE_DEVICES'] = '1... | test/test-melgan.ipynb |
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#export
import torch
# +
# default_exp functions
# -
... | notebooks/00_functions.ipynb |
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import pandas as pd
df_morning = pd.read_csv('dat... | cs224w/TCDF-test1.ipynb |
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# importacion general de librerias y de visualizac... | TP2/Alejo/3_XGBOOST_hashtag_encoding.ipynb |
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# + [markdown] id="9MM5cpotg1r-"
# This is a companion... | chapter02_mathematical-building-blocks.ipynb |
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# + colab={} colab_type="code" id="oW0JBwpOCSGs"
"""
... | DCGAN/MNIST_GAN_v1.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | module3-ridge-regression/Copy_of_LS_DS_213_assignment.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | House_Price_Prediction.ipynb |
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# # Unsupervised Learning
#
# In unsupervised learning,... | examples/clustering/clustering.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Transformers_Sentiment_Analysis.ipynb |
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import paper
import database
import importlib
imp... | .ipynb_checkpoints/Networkx fiddling-checkpoint.ipynb |
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import pandas as pd
import numpy as np
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# Activiti... | HRA_LSTM2.ipynb |
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# ### Deutsch-Jozsa algorithm
#
# The [Deutsch-Jozsa a... | Notebooks/Deutsch-Jozsa_algorithm.ipynb |
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import multiprocessing as m
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# + colab_type="code" id="6q7dDydT7n2d" outputId="be47... | pytorch/Seq2SeqForTranslation.ipynb |
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# %matplotlib inline
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# # The mplot3d Toolkit
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# ... | python/learn/matplotlib/tutorials_jupyter/toolkits/mplot3d.ipynb |
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# + [markdown] id="3xEPIoQ2VdUI"
# ## Heart Disease Prediction
# + id="2Daqk... | Heart_Disease_Prediction.ipynb |
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# # PyFME Validation : comparing response with eigenva... | .ipynb_checkpoints/PyFME vs Eigenvalue analysis-checkpoint.ipynb |
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# <!--BOOK_INFORMATION-->
# <img align="left" style="padding-right:10px;" src... | notebooks/04.00-Numerical-Computation.ipynb |
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# # Inferential Statistics Report
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# In this brief do... | reports/Inferential-Statistics-Report.ipynb |
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# # FashionMNIST
# Load images from the [Fashion-MNIST... | 03_Fashion_MNIST/FashionMNIST.ipynb |
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# # Inspecting training data
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# ## Backg... | testing/southern_cropmask/2_Inspect_training_data.ipynb |
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# !pip install pandas
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#all_slow
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# 1. Adapt the Gradient_univ for polynomial 2x**2 +2x ... | Exercises/DaigleGradientDescentExercise.ipynb |
# -*- coding: utf-8 -*-
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# # Wiki whā (4) tutorial Python notebook
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# Use t... | Wiki_wha_sln.ipynb |
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... | notebook/Unzip - Zip folders.ipynb |
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# ## Coach Instructions
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# This Python notebook can be used before the Hack to prepare data files for the participants. The intent is for th... | 024-DoYouEvenSynapse/Coach/Resources/Lab Data Prep.ipynb |
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#... | tutorials/Supplementary Primer Tutorial 1 - Effects of Suboptimal Architecture on Functional variant characterization for non-coding SNPs within the SPI1 motif.ipynb |
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# # VacationPy
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# #### Note
# * Instructions h... | VacationPy.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# # Local Image Classification Training - Bars
#
# Cla... | Chapter3/Bar Categorization/Bar Categorization-VGG19-nolast.ipynb |
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# # Spark tutorial
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# ## Setup
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# # Evil solu... | 2016/jordi/Day 1 - Evil solution in one line.ipynb |