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# # Logistic Regression 3-clas... | 04 Lineal Regression/.ipynb_checkpoints/plot_iris_logistic-checkpoint.ipynb |
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########### Banco de dados... | 04_aprendizagem-baseada-em-instancias/KNN_bank_full.ipynb |
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# + id="PF219yewQCuv"
import pandas as pd
import numpy as np
import seaborn a... | alura_estatistica_probabilidade.ipynb |
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# + [markdown] id="vl-0acX6FBQu"
# # This notebook describes how the FruitNet... | notebooks/FruitNetTransferLearning.ipynb |
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# <a href="https://colab.research.google.c... | BME511/SystemIdentificationMAP.ipynb |
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# ## Week 8: Reinforcement Learning for seq2seq
#
# Th... | Practical_RL/week8_scst/practice_tf.ipynb |
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# # Library imports
# +
#usual imports
im... | 03-Walmart Sales/walmart_store.ipynb |
# Assignment: Linear regression on the Advertising data
# =====================================================
#
# **TODO**: Edit this cell to fill in your NYU Net ID and your name:
#
# - **Net ID**:
# - **Name**:
# To illustrate principles of linear regression, we are going to use some
# data from the textbook “... | notebooks/2-advertising-hw.ipynb |
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# # Predicting Survival on the Titani... | Predicting Survival on the Titanic.ipynb |
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# # Analyze target statistics
import matp... | src/notebooks/targets/target_stat.ipynb |
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# ## Connect and Manage an Exist Experiment
# ### 1. C... | docs/zh_CN/Tutorial/python_api_connect.ipynb |
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import os
os.environ['PYSPARK_SUBMIT_ARGS'] = \
'--c... | workshop/Lambda - Batch - Users who bought X also bought ....ipynb |
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# <div style="text-align: center;">
# <h2>INFSCI 2915 ... | assignment1/YUHAO_WU-yuw121-Assignment1.ipynb |
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# import necessary packeges
# %matplotlib inline
f... | Part 4 - Fashion-MNIST.ipynb |
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# + id="C66HXNKf2Kl5" colab_type="code" outputId="d7b3d35a-f74f-41ba-db23-67e... | day3_simple_model.ipynb |
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# ###### Content under Creative Commons Attribution li... | notebooks_en/3_Multiple_Linear_Regression.ipynb |
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# + [markdown] papermill={"duration": 0.017282, "end_t... | filter/spark-sample.ipynb |
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# + [markdown] id="6rqSTOHXHN3f"
# **Припустимо, що у вас є багатошаровий пер... | semester7/nn/seminar4.ipynb |
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# The purpose of this file is to load World bank indic... | notebooks/data_gathering/world_bank_bulk_csv.ipynb |
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import numpy as np
import json
import pandas as pd
imp... | Notebooks/TestGTtoJSON.ipynb |
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# # Feature Visualization
# This notebook will go thro... | notebooks/feature visualization.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | coursework_data.ipynb |
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# # User guide and example for the Landlab SPACE compo... | notebooks/tutorials/landscape_evolution/space/SPACE_user_guide_and_examples.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Part 03/Lab 02/ammi_dnlp_lab2.ipynb |
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import sunpy
from sunpy.net import hek, helioviewer
fr... | notebooks/Untitled.ipynb |
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# %matplotlib inline
# %config InlineBackend.figur... | DataScience_Project1_Predict_products_sales_in_Walmart/2018_07_01_DSS_Project1.ipynb |
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# # A beginner's guide to PySDDR
# We start by import... | tutorials/BeginnersGuide.ipynb |
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# # King County House Price Prediction
# ## Abstract
... | Assignment1_King_County_Price_Predication.ipynb |
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# Scikit Learn
# -
import pandas as pd
print(pd._... | backup/11.sklearn21.ipynb |
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# # Time Series - Lecture 1: Introduction
#
# ## Agend... | Time Series Analysis - Lecture 1.ipynb |
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# <img src="../../images/qiskit_header.png" alt="Note:... | qiskit/fundamentals/7_summary_of_quantum_operations.ipynb |
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# # !pip install ... | txfer/txfer_eval.ipynb |
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# # Material
# ```
# Material(params: Dict, r... | docs/notebooks/03_Material.ipynb |
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# + [markdown] id="NpnZ0Rf2ZBPd"
# top 은 가장 많이 카운팅 된 것의 값들을 말한다.
#
# freq은 가장... | 1_datapreprocess_fillna.ipynb |
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# %matplotlib n... | msfr/plots/MSFR_reprocessing_SCALE-ChemTriton.ipynb |
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# # Modeling and Simulation in Python
#
# Rabbit examp... | code/rabbits3-Mine.ipynb |
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import os
import json
import numpy as np
import matplo... | notebooks/single_element_conditioning_analysis.ipynb |
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# + [markdown] colab_type="text" id="IYfWdgdIG_yb"
# #... | _notebooks/2020-06-12-tfkeras-pytorch-cifar10.ipynb |
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# # Twitter Sentiment Analysis Project
#
# ## Part I -... | TwitterSentimentAnalysis/MSDS_Project_Twitter_Sentiment_Analysis.ipynb |
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# # Unity ML-Agents Toolkit
# ## Environment Basics
# ... | notebooks/getting-started.ipynb |
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# This notebook is designed to run in a IBM Watson S... | scalable-machine-learning-on-big-data-using-apache-spark/Week 3/Exercise 2 - Working with Clustering and Apache Sp.ipynb |
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# # Current time
# !date
# # Collect all relevant tw... | other/tcr-name-giveaway/Pick MC38B TCR name winners.ipynb |
# ##### Copyright 2021 Google LLC.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writ... | examples/notebook/examples/linear_programming.ipynb |
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# # Lecture 8: p-hacking and Multiple Comparisons
# [<NAME>](https://git... | lecture-10-multiple-comparisons.ipynb |
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# # Timeseries plot (swimla... | EcoFOCI_Moorings/ERDDAP_Automated_Tools/MooringErddapTimeLine.ipynb |
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# + [markdown] Collapsed="false" slideshow={"slide_typ... | m05_data_science/m05_project02/m05_project02.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Final_Exam.ipynb |
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# # Formal Grammars
from numpy.random import choice
# ## U... | book/4_lab.ipynb |
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import matplotlib.pyplot as plt
import... | experiments/global_sensitivity/Fully Connected Upstream Clipping MNIST.ipynb |
# -*- coding: utf-8 -*-
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# # Data visualization
library(tidyverse)
# Ig... | notebooks/wpa3_answers.ipynb |
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import tensorflow as tf
from tensorflo... | source/VGG19/VGG19_pretrained_t2_frontal.ipynb |
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# <h1 align="center">Dinámica</h1>
# <h1 align="center... | C03_CinematicaCineticaParticulas_MovParabolico.ipynb |
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CRISP_DM = "C:/Users/kaivl/data_science_covid-19/CRISP... | notebooks/3. Data Preparation.ipynb |
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# # Computing gradients in parallel with Penn... | pennylane/1_Parallelized_optimization_of_quantum_circuits.ipynb |
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# ##### argument (인자)
# 함수를 호출할 때 함수 (또는 메서드) 로 전달되는 값... | Python - Term.ipynb |
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import os
import sys
import math
import logging
fr... | notebooks/template.ipynb |
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# # Crypto Data Download
# %config IPCompleter.greedy... | crypto_data_download.ipynb |
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#pytorch version 0.4.1
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# !export PYTHONPATH=$... | molvae/Test_Task_GM.ipynb |
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import matplotlib.pyplot as plt
from mpl_toolkits.... | nb/pca/PCAofMultiNormal.ipynb |
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# # Nothing But NumPy: A 2-layer Binary Classification... | Understanding_and_Creating_Binary_Classification_NNs/2_layer_toy_neural_network_on_all_iris_data.ipynb |
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import pandas as pd
df = pd.DataFrame({
'City': [... | day9/warm-up-day-9-ex2-solution.ipynb |
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# # Analyzing COVID-19 Papers
#
# In this challenge, we wi... | 2-Working-With-Data/07-python/notebook-papers.ipynb |
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# # Hierarchical Partial Pooling
# Suppose you are ta... | docs/source/notebooks/hierarchical_partial_pooling.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Day_5_Max_Profit.ipynb |
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# # A simple function with different types of input pa... | examples/Simple_Function.ipynb |
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def strToBinary(strg):
c = list(strg)
result =... | Security/Stream_Cipher/Streamer.ipynb |
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# + language="html"
# <script>
# function getToken() {... | examples/token_demo.ipynb |
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# # This notebook is specifically made for Python3.x v... | _src/Section 7/7.1 Currying in Python 3.ipynb |
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# ## Simulation of a M/M/1 queue using processes
... | SP/mm1.ipynb |
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# + [markdown] id="C1QVJFlVsxcZ"
# # Preface
#
# <br>
# <div style="font-vari... | docs/notebooks/linen_intro.ipynb |
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# name: python3-azur... | .ipynb_aml_checkpoints/07 - Work with Compute-checkpoint2021-9-8-1-29-42Z.ipynb |
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# + [markdown] id="HbOKBdp_r8WW"
# # Semester Project
# ## How much corn syru... | group6_finalproject-colab.ipynb |
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# # Implementation of HED in Pytorch
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# im... | train.ipynb |
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# # 1.1 Finite Difference Formulation
# Prepared by (... | 1.1 Finite Difference Formulation.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Lab_Notebooks/S2_2_Training_Models.ipynb |
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# <img style='float: left' width="150px" src="http://b... | web-services/01-skill_score.ipynb |
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# # Credit Scoring Model
import pandas_datareader as ... | Credit_Scoring.ipynb |
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from datetime import timedelta , datetime
import numpy... | code/SIARD_KOREA_PREDICT.ipynb |
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# # KNN From Scratch
# ## Imports
from sklearn impor... | notebooks/KNN From Scratch.ipynb |
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# # Module 2: Basic data structures and containers
# ... | week2/week2_2_basic_structures_containers.ipynb |
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# # Implementation of Multilayer Perceptrons from Scratch
# :label:`sec_mlp_scratch`
#
# Now that we have characte... | d2l/pytorch/chapter_multilayer-perceptrons/mlp-scratch.ipynb |
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# # Fuzzy Logic Inference
# ** textbook question 7.5 (... | q7.5.ipynb |
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import os
out = 'xlnet-base-bahasa-cased'
os.make... | pretrained-model/xlnet/huggingface/save-huggingface.ipynb |
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# # 创造最大的数
#
# [![Author](https://img.shields.io/badge... | March/Week12/82.ipynb |
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# The normal equation
import numpy as np
import m... | notebooks/ch_04_training_models.ipynb |
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# ## Generate handwritten digits with trained CVAE net... | demo-mnist/notebook-cvae-mnist-gen.ipynb |
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# + [markdown] colab_type="text" id="oL9KopJirB2g"
# #... | site/ja/tutorials/load_data/unicode.ipynb |
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# name: conda-env-parcels-cont... | notebooks/exploratory/114_afox_plottracks_rockallbank.ipynb |
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# ... | dmu4/dmu4_sm_ELAIS-N2/generate_holes.ipynb |
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# # Import the necessary libraries
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import numpy a... | Decision_Trees/Basic/Decision_Trees.ipynb |
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# # Working with supply data
#
# COVID Care Map has co... | notebooks/00_getting_started/01_Working_with_supply_data.ipynb |
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import sa... | .ipynb_checkpoints/tensorflow-sagemaker-env-checkpoint.ipynb |
# -*- coding: utf-8 -*-
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#ロケットのタイムステップは100
ts.length <- 100
# 運動は加速度で駆動さ... | notebooks/Ch07/chap7.ipynb |
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... | CreditCardDef.ipynb |
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#Load Libraries
import numpy as np
import pandas as pd... | Major_Project.ipynb |
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import numpy as np
import pandas as pd
from sklea... | main.ipynb |
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# + [markdown] button=false new_sheet=false ... | Logistic-Reg-churn.ipynb |
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# # Inverse Transform Sampling: Logistic Distribution
... | tf-change-of-variables/main.ipynb |
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import pandas as pd
import numpy as np
import os, ... | Preprocessing.ipynb |