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# %matplotlib inline
import numpy as np
im... | cj2-8.ipynb |
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import sys, os, _pickle as pickle
import tensorflo... | LCA Shortest Path/modelv8.ipynb |
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# # Assignment Question 4
# The digital root of a num... | Untitled4.ipynb |
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# + [markdown] pycharm={"name": "#%% md\n"}
# # Pipeli... | tutorials/Tutorial11_Pipelines.ipynb |
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# Install if Open... | Chapter02/OpenPyXL_example.ipynb |
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# + pycharm={"is_executing": false}
# print
fname = 'S... | Slides/1_Output_function.ipynb |
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# # Scikit-learn
#
# This example shows ho... | notebooks/integrations/integration-sklearn.ipynb |
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class Debug:
def __init__(self, level):
se... | directme/analysis/Gov16_dataAnalysis.ipynb |
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# # Cluster analysis
#
# In this notebook, we will loo... | docs/tutorials/clusters.ipynb |
# # Linear regression with non-linear link between data and target
#
# In the previous exercise, you were asked to train a linear regression model
# on a dataset where the matrix `data` and the vector `target` do not have a
# linear link.
#
# In this notebook, we show that even if the parametrization of linear models
#... | notebooks/linear_regression_non_linear_link.ipynb |
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# # Describing GMAW processes
# ## Imports
import weldx
f... | tutorials/GMAW_process.ipynb |
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# # Get the HPS model to run
# - get the inputs correc... | Analysis/hps_STRICT.ipynb |
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# #### FP-Growth Algorithm Model on 30% of the Data
#... | model/fp_model_30_percent_data.ipynb |
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# # Randowm Walk
import matplotlib.pyplot as plt
# %m... | Untitled9.ipynb |
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# %%time
# %matplotlib inline
import n... | notebooks/exploration_transformacion.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Assignment_5.ipynb |
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# # Loading large datasets
#
# **Learning Objectives**... | courses/machine_learning/deepdive/02_tensorflow/labs/d_csv_input_fn.ipynb |
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# # Word Embeddings : le modèle Word2Vec
... | module4/s4_word_embeddings_2.ipynb |
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from numpy.core.numeric import outer
from scipy.sp... | multimodal/graph/hetero-gat-based/Untitled.ipynb |
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# import sys
# from pathlib import Path
# import numpy as np
#... | tests/profiling.ipynb |
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##SHORT VISUAL ANALYSIS
# Maximum city temperature... | lat_cities_data_analysis.ipynb |
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/ + [markdown] azdata_cell_guid="d292b1ed-5648-4fae-b31c-9504c665ff... | Notebooks/Books/DiagnosticBook/content/whoisactive/INSTALL.ipynb |
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# # Recovering columns hidden by the 🤗 Trainer
#
# -... | _notebooks/2021-01-15-til-recovering-hidden-trainer-columns.ipynb |
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# # Azure Automated ML
import azureml.core
import ... | utf-8''automl.ipynb |
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# **Question1**
# <br>Create a function that takes a s... | Python Programming Basic Assignment - Assignment19.ipynb |
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# # Generative Adversarial Neural Network for the MNIS... | gan/mnist_dcgan.ipynb |
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import matplotlib.pyplot as plt
import cv2
import ... | exercise1_dataformat.ipynb |
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import pandas as pd
import numpy as np
# %matplotlib ... | SSL Skater Model Interpretation.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Elephas_Keras.ipynb |
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# # Data Preprocessing Module
# In this tutorial, fun... | docs/notebooks/Data_Preprocessing_Module.ipynb |
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# # <img style="float: left; padding-right: 10px; widt... | content/lectures/lecture03/cs109b_lab1_B_statsmod_2021.ipynb |
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import ipywidgets as widgets
from IPython.display ... | sample_windows1.ipynb |
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# ###### Content under a Creative Commons Attribution ... | lessons/07_Lesson07_methodOfImages.ipynb |
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# + [markdown] id="vsWmY-o31SLT"
# I <NAME> declare that the work done in thi... | assignment1/assignment1.ipynb |
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import pandas as pd
import pandas_datareader.data as w... | Perfiles de Inversionistas.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | StockPricePrediction_.ipynb |
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# ## Seaborn-Pokemon
#
# In this Jupyter Notebook I wi... | seaborn-pokemon.ipynb |
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import pandas as pd
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import mat... | example1/Untitled.ipynb |
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# # Loading data into StellarGraph from Pandas
#
# > T... | demos/basics/loading-pandas.ipynb |
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from bokeh.plotting import figure, save, show, output_... | ms_project.ipynb |
# -*- coding: utf-8 -*-
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# # R for Drug Development
# ![](http://www.osd... | R for Drug Development - National Survey on Drug Use and Health, 2012.ipynb |
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# Import dependencies
from splinter import Browser
fro... | .ipynb_checkpoints/mission_to_mars-checkpoint.ipynb |
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# + [markdown] id="bhWV8oes-wKR"
# # COURSE: A deep understanding of deep lea... | 04_Overfitting_n_CrossValidation/DUDL_overfitting_scikitlearn.ipynb |
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a = input('enter a number : \n')
print(a)
print("Ente... | Python for Everybody Exploring Data Using Python 3 Charles R. Severance.ipynb |
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# ### Note:
# This notebook is aimed at getting a hand... | sf/grid_experiments/fft_visualization.ipynb |
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# # Find PI to the Nth Digit - Enter a number and have... | Find PI to the Nth Digit.ipynb |
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# # https://github.com/kernoelpanic/smartenv
# # Smar... | course/sccc.ipynb |
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# ## 17.3.1 Visualizing Word Frequencies with Pandas
#... | examples/ch12/snippets_ipynb/12_03.01.ipynb |
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import matplotlib.pyplot as plt
max_frequ... | triton/Nano MobileNet.ipynb |
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# <table style="float:left; border:none">
# <tr sty... | tutorial/03 - Data Sources and Transformations.ipynb |
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#importing some useful packages
import matplotlib.pypl... | Threshold Binary Images.ipynb |
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import torch
import torchvision
import torchvisio... | .ipynb_checkpoints/Analysis -checkpoint.ipynb |
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# ### T-SNE
# * t-SNE is a nonlinear embedding algori... | theory/T-SNE.ipynb |
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# # Project: Identify Customer Segments
#
# In this pr... | Identify_Customer_Segments.ipynb |
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-- # Visualizing Data
--
-- ## Line Chart... | notebooks/03 - Visualizing Data.ipynb |
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# ### 1. In this scenario, two friends are... | python-crash-course/week-2/quiz-expressions-and-variables.ipynb |
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import os
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i... | SVM.ipynb |
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# # 根据方差筛选出来的重要app
# coding=utf-8
import numpy as np
... | src/category_activated_4000.ipynb |
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# Contenido bajo licencia Creative Commons BY 4.0 y có... | notebooks/04_mallas.ipynb |
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# # Lecture 0. Basics
# ## Before Python, what is a J... | Lectures/Lecture_0_Basics.ipynb |
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from tensorflow.keras.applications import ResNet50... | AllCodeForCOVID/covid_res50.ipynb |
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import pandas as pd
import numpy as np
import swif... | notebooks/preprocessing/protein_preprocessing_original.ipynb |
# -*- coding: utf-8 -*-
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# # This sage worksheet acc... | manin_constant/lattices_of_modular_forms.ipynb |
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# ## Gather recent Twitter data
import tw... | code/Pull recent data.ipynb |
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import numpy as np
import matplotlib.pyplot as pl
... | utils/test gammatones.ipynb |
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# # Building Predictive Models
import pandas as pd
im... | notebooks/3.0-ak-building-predictive-model.ipynb |
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# pip install lyricwikia
# pip install access-spot... | AlbumInfoGeniusSpotifyScrawler-Copy3.ipynb |
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import numpy as np
import matplotlib.pyplo... | calc_pulse_integral_amplitude.ipynb |
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# # Fundamentos de Python
#
# ## Módulos e pacotes
# ... | Cap04/Notebooks/.ipynb_checkpoints/Untitled2-checkpoint.ipynb |
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# # Lab 1: Introduction to Python
# Machine Learning 2... | week1/intro1-python.ipynb |
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# # ANOVA over all DBS configurations for a specific walk... | analysis/notebooks/01_anovas_per_patient.ipynb |
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# + [markdown] colab_type="text" id="view-in-github"
# <a href="https://colab... | content/06_other_models/05_svm/colab.ipynb |
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# + [markdown] colab_type="text" id="OO-TE-7FYlAt"
# #... | bootcamp_igti/02_analise_dados/02_aula_interativa.ipynb |
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# # PROBLEMAS DIVERSOS
# <h3>1.</h3>
# Realizar una f... | Modulo2/Ejercicios/Problemas Diversos.ipynb |
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# + [markdown] pycharm={"name": "#%% md\n"}
# ## FastB... | chapter9/Fast_bert_.ipynb |
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# <!-- dom:TITLE: Data analysis and Machine Learning ... | doc/pub/Linalg/ipynb/Linalg.ipynb |
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# # Advent of code 2021
#
# ## imports
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import re
f... | scripts/aoc/Advent_of_code_2021.ipynb |
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# Gesture Typing
# ===
#
# Typing quickly and accurat... | ipynb/Gesture Typing.ipynb |
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# + slideshow={"slide_type": "skip"}
import numpy as n... | Sessions/Session08/Day2/CorrallingUnrulyData.ipynb |
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# # Examples
# ## indices
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import numpy as np
from... | docs/examples.ipynb |
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# ## Simple Linear Regression ( Minimal example)
# E... | Simple Linear Regression. Minimal example.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | support_vector_regression.ipynb |
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import requests
import re
import time
import r... | history_search/dmhy_update_all.ipynb |
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# # UNSEEN-open
#
# In this project, the aim is... | doc/_build/.doctrees/nbsphinx/Notebooks/Workflow.ipynb |
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# # Collection of Helpful Functions for [Class... | jeffs_helpful.ipynb |
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# This is a simple performance test to verify in pract... | tests/PerformanceTest.ipynb |
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# ## Week Five
#
# ### Lists
#
# __Sequential Ordered ... | All iPython Notebooks/_2_BAMM_101_W_2_Lists-Dicts-daytime.ipynb |
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# # IOT and Computer Vision Task 1:
#
#
# ## Color Ide... | Task#1 .ipynb |
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#Add needed imports
import numpy as np
import pand... | project/notebooks/Dataset1/Dataset1 - Churn Prediction.ipynb |
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# # Validation and Model Selection
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# -*- coding: utf-8 -*-
""" Convolutional network... | Lectures/Lecture-08/Untitled.ipynb |
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# # Clean up existing Kind cluster
# !kind delete clu... | docs/notebook/kuberay-on-kind.ipynb |
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# + raw_mimetype="text/restruct... | doc/tutorial/color_palettes.ipynb |
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# + [markdown] id="supported-drill"
# # Dataset
# + i... | docs/notebooks/functorial_language_model.ipynb |
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def fact(n):
output = 1
for i in range(1, n+1)... | python practice/pypthon practice 4.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# # Setup
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### Libraries
import pandas as pd
from ... | jupyter-samples/IntegeratedML-Monitor-Example-Simplified.ipynb |
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# # Code to compare Price of product on two different ... | prod_price_in_ipy.ipynb |
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subjects_dir = "/"
subject_id = "0040013"
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from ni... | rmi.ipynb |