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# name: python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:ap-south... | notebooks/part0-setup.ipynb |
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# # Mandelbrot set - Sinusoidal
# Import ... | notebooks/Mandelbrot_sinusoidal.ipynb |
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# # QUICK REVISION NOTES
# ## 1. INTRODUCTION TO PROG... | Python/001. Introduction to python and essentials.ipynb |
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# ## Método de aceptación rechazo
#
# Este método surg... | TEMA-2/Clase10_MetodoAceptacionRechazo.ipynb |
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# ## Preprocessing
# +
# Impor... | Starter_Code.ipynb |
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# ## Machine Learning Model Building Pipeline: Feature... | Section-2-Machine-Learning-Pipeline-Overview/Machine-Learning-Pipeline-Step3-Feature-Selection.ipynb |
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i... | main.ipynb |
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# + id="TCVgYdgSOD31" jupyter={"outputs_hi... | Notebooks/MARBERT-FineTuning.ipynb |
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# _Python_ package [neurolab](https://gith... | Practica 3/Practice_03_ANN.ipynb |
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# ![Egeria Logo](https://raw.githubusercontent.com/odp... | open-metadata-resources/open-metadata-labs/egeria-server-config.ipynb |
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# # Traffic Flow Model
# ## Goal
# The goal... | .ipynb_checkpoints/Traffic_Flow_Model-checkpoint.ipynb |
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# + executionInfo={"elapsed": 8976, "status": "ok", "t... | cases/Booking.com/reco-session-booking-02.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="IvHLIW5VrjFz" outputId=... | 01_python_basics.ipynb |
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import pandas as pd
import numpy as np
import kera... | 4.ipynb |
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# + id="86lINDr_mQD1" colab_type="code" colab={"base_uri": "https://localhost... | Notebooks/1) Accessing_Data.ipynb |
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# %load_ext autoreload
# %autoreload 2
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import num... | nbs_gil/data_science_bowl/data_science_bowl_training_19_regression_lgb.ipynb |
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from sympy import symbols,solve
import numpy a... | Fiedler_revised/n060_sympyschemes.ipynb |
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# + [markdown] id="5D3U6h6e3HBz" colab_type="text"
# N... | Upc/Deep_Learning_Days_1-5/aidl2019_dl_lab3_cnn.ipynb |
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# # Custom Model Training
# Use the Azure Machine Lea... | workbench/training.ipynb |
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# azureml-core of version 1.0.... | 01. Using Azure Machine Learning/05. The AzureML SDK/Automl.ipynb |
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# ### Importing Libraries
import pandas as pd
from sk... | cleaning.ipynb |
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# # (baseline development) Silicon per M2 Calculations... | docs/tutorials/baseline development documentation/(baseline development) Silicon per m2.ipynb |
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from pathlib import Path
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impo... | experiments/axon_geometry/notebooks/autocorrelation.ipynb |
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# # First Prototype Without NLP
# ## Import relevant ... | notebooks/4.0-cgb-firstprototypewithoutnlp.ipynb |
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# hash: 5f51ddfaf8b2bda7e9920d2fe19bd5c12735de5d... | HAFTA-6/DERS-16/OOP/oop1.ipynb |
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# # Porcess news information
import requests
import re... | SinaFin.ipynb |
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import pandas as pd
df = pd.DataFrame(["male", "MALE"... | hearts_full_of_pride/Untitled1.ipynb |
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# + [markdown] tags=["module-nm"]
# (nm_linear_algebra... | notebooks/c_mathematics/numerical_methods/11_linear_algebra_intro.ipynb |
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import sys
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import pa... | lobpredictrst/run_model.ipynb |
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import torch
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import torch.optim ... | ml/pytorch/init_env/overfitting_contorl.ipynb |
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# # TASK 5 - MILESTONE 2
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# # Packages used for ... | Milestone 2/.ipynb_checkpoints/TASK 5 - MILESTONE 2-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | part2/MRL_Dataset_CNN_Classification.ipynb |
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# # $I_{Na,t}$ модель (заготовка для заполнения)
# %p... | I_Na,t-stub.ipynb |
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# # Regulome Explorer Notebook
#
# This notebook comp... | RegulomeExplorer/RegulomeExplorer-notebook.ipynb |
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from hyppo.ksample import KSample
from hyppo.independence i... | summary/summary_statistics.ipynb |
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import keras
from keras.datasets import fashion_mnist ... | CNNs on Fashion mnist.ipynb |
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# # MATH50003 Numerical An... | sheets/week3.ipynb |
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# # NIPS impementation challenge: "Concentration of M... | NIPS_Ising.ipynb |
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-- + [markdown] ... | notebooks/IHaskell.ipynb |
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# coding:utf-8
from __future__ import print_function
i... | ed_sz_conserved_1d_heisenberg_py.ipynb |
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import string
from collections impo... | main2.ipynb |
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import pandas as pd
df = pd.read_csv('survey_results_... | Python Library/intro_to_numpy_pandas_matplotlib/Learning_pandas1..ipynb |
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# # Welcome to the Awesome-sauce, let be your guide to... | presentations/10_11_19_Anthony.ipynb |
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# # Sparkify 项目 Workspace
# 这个 Workspace 包括一个迷你的子数据集（1... | Sparkify-zh.ipynb |
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# <img src="animated.gif" width=500>
#
# # How to make... | notebooks/misc/Making an animated GIF.ipynb |
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# # Data Types
#
# When reading in a data set, pandas ... | lessons/ETLPipelines/7_datatypes_exercise/7_datatypes_exercise.ipynb |
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#IMPORTACIÓN DE LIBRERÍAS
import pandas as pd
import n... | notebooks/titanic_analysis.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Simulation/Random_walk.ipynb |
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from shapely.geometry import Point, Polygon
import... | notebooks/.ipynb_checkpoints/modeling_block0-checkpoint.ipynb |
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# # 2. Interacting with APIs to import data from the w... | Data Analyst with Python/10_Intermediate_Importing_Data_in_Python/10_2_Interacting with APIs to import data from the web.ipynb |
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import nltk
#nltk.download('wordnet')
from nl... | notebooks/approaches.ipynb |
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# + [markdown] slideshow={"slid... | 31_approximation.ipynb |
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# # Generate Random Networks Based on Delaunay Triangu... | examples/notebooks/networks/generation/random_networks_based_on_delaunay_and_voronoi_tessellations.ipynb |
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# ### How to run pulsequantum from ipython notebook
#... | docs/example_notebooks/How_to_run_pulsequantum_from_ipython.ipynb |
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import pandas as pd
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from IPython.di... | other/pattern_classification/matplotlib_viz_gallery.ipynb |
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# # Seldon Kafka Integration Example with CIFAR10 Mode... | examples/kafka/cifar10/cifar10_kafka.ipynb |
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# #Strings
# Strings are used in Python to record tex... | notebooks/Complete-Python-Bootcamp-master/Strings.ipynb |
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# <a href="https://colab... | module3-basicdatavisualizations/LS_DS_113_Plotting_Playground.ipynb |
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# # Plan for Python work
#
# 1) My _suggestion_ is to ... | Wi19_content/DSMCER/L8_SubsetRegularization.ipynb |
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# <img src="https://github.com/OpenMined/design-assets... | examples/pygrid/homomorphic-encryption/Tutorial_2_TenSEAL_Syft_Data_Owner.ipynb |
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# ## View movie rating data
import pandas
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# # Xarray Tutorial
#
# <div class="alert-info">
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# #... | xarray.ipynb |
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# # 3. Quantum mechanics
#
#
# Quantum mechanics is a ... | community/awards/teach_me_quantum_2018/intro2qc/3.Quantum mechanics.ipynb |
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# # Configuring a Spark session using configure-f
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# ### Import Library
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import cv2
import glob
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from... | jupyterhub/notebooks/transcode_video_to_jpeg.ipynb |
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# 「PyTorch入門 2. データセ... | notebook/0_Learn the Basics/0_2_data_tutorial_jp.ipynb |
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# # Analyzing Trajectory
# ### Running an MD simulati... | Trajectory Analysis.ipynb |
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# <a href="https://colab.research.google.com/github/in... | AnalisisDeDatos/4_Data_Wrangling_Avanzado/ejercicio/ejercicio.ipynb |
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# numpy efficiently deals with numerical multi-dimensi... | tensorflow.ipynb |
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q = p
p = sorted([(str(x[0]), x[1]) for x... | Untitled.ipynb |
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# # Projeto Ciência de Dados - Previsão de Vendas
#
# ... | programas/ciencia-de-dados/ciencia-de-dados.ipynb |
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# !git clone https://github.... | exp60p/colab.ipynb |
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# # Tracking
#
# ## 概述
#
# 使用类继承的方法，无... | hw2_1/jupyter/Tracking.ipynb |
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# # INFO 3350/6350
#
# ## Lecture 05: Sent... | lectures/lec-05-sentiment.ipynb |
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# # Spark DataFrames
#
# Use Spakr DataFrames rather ... | notebooks/.ipynb_checkpoints/S15C_Spark_DataFrames-checkpoint.ipynb |
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# + [markdown] id="2EtmGlmK4pAa"
# # DCN on Criteo Ad Dataset in TF 2.x
# + ... | _notebooks/2022-01-19-dcn.ipynb |
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# Node
class Node():
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# necessary imports
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# <img src="http://www.exalumnos.usm.cl/wp-content/upl... | Aprendizaje Supervisado/Otros/Regression.ipynb |
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# # Layered objects examples
... | notebooks/DetectObjects.ipynb |
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# # Fire up graphlab create
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# <h1><b>Lab 3</b></h1>
# <h1>PHYS 580 - Co... | Labs/Lab03/Lab3out.ipynb |
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# Really simple PD control for the "reacher" s... | old/reacher/reacher.ipynb |
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# + [markdown] _cell_guid="b1076dfc-b9ad-4769-8c92-a6c... | chapter_08/tutorial-bayesian-optimization-with-lightgbm.ipynb |
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# title: "Create Baseline Regression Model"
# author: "<NAME>"
# date: 2017-12-20T11:53:49-07:00
# description: "How to create a baseline regression model in scikit-learn for machine learning in Python."
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# # Popups
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# It is possible to display the informati... | examples/03_visualizations/02_popups.ipynb |
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# Let us create some RDDs
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# USAGE
# python train.py --dataset dataset
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