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import numpy as np
x = np.arange(-6, 6, 0.001)
import... | Chapter 8/Sigmoid.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="h... | Lab2/Lab2.ipynb |
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# ## AI for Medicine Course 3 Week 2 lecture notebook ... | AI for Medical Treatment/Week 2/lecture_notebooks/AI4M_C3_M2_lecture_notebook_clean.ipynb |
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# %matplotlib inline
#
# # Libsvm GUI
#
#
# A simple ... | Python-sklearn/svm/svm_gui.ipynb |
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# # Lecture 12 – More Iteration
#
# ## Data 94, Spring... | lecture/lec12/lec12.ipynb |
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from bs4 import BeautifulSoup
import requests
import p... | wikipedia_crawling/wikipedia_get lyrics.ipynb |
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# # 17장. 시계열 분석
# # 17.1
# ## 위키피디아 페이지뷰 API 만료로 이 ... | Chapter 17.ipynb |
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# # Simple Linear Regression
# #### - Peprocessing
... | Regression/Linear_Regression.ipynb |
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print('Meu nome é: <NAME> ')
print('Meu RA é: 192801')... | CIFAR_10/Other_pytorch/my_logistic_regression_iris.ipynb |
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import sys, os, glob
import numpy as np
import pan... | SMG-bud-count-Ecad-integrin-blocking-antibody.ipynb |
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# + [markdown] heading_collapsed=true
# #### Libraries... | Untitled.ipynb |
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'''
Numbers:
Integers
You can use an integer repre... | 01 Introduction to Python/02_number_ops.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # M... | ML_Regression_Tutorial_Lynn.ipynb |
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# %matplotlib inline
# %config InlineB... | docs/notebooks/mask_2D.ipynb |
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import numpy as np
import pandas as pd
from sklearn i... | Kaggle/Tweet NLP 2.ipynb |
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import collections
# ## part 1 ##
testlines = '''001... | day3.ipynb |
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# + [markdown] tags=["remove_cell"]
# <a... | reports/report/01.1.report.ipynb |
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# This notebook was prepared by [<NAME>](https://githu... | graphs_trees/bst/bst_solution.ipynb |
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# <table><tr>
# <td style="background-color:#ffff... | silver/S01_References.ipynb |
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import numpy as np
import pandas as pd
import ... | challenge_rythm_Belkhayat_Feltin.ipynb |
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import os
path_parent = os.path.dirname(os.getcwd())
o... | notebooks/biogas_developement.ipynb |
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# + [markdown] nbgrader={}
# # Project Euler: Problem ... | assignments/assignment02/ProjectEuler2.ipynb |
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import os
import torch
from torch import nn, optim
fro... | scripts/Linear-VAE-baseline-MNIST.ipynb |
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# # Day 6
# ## Part 1
from copy import deepco... | Day 6.ipynb |
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import wandb
wandb.init(project="pytorch-ignite-exampl... | notebooks/wandb/run-20200131_192656-b1wh3rz5/code/notebooks/1.1_First_neuralnet_trying wandb.ipynb |
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# Script for training a denoiser on KappaTNG
impor... | notebooks/KappaTNG_COSMOS_emulation.ipynb |
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#libraries
import glob, os
import re
import random... | applications/matrix_example/experiment_helper/LIKWID_group_generator.ipynb |
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# %pylab
# %matplotlib inline
# ## 切片、提取、赋值、索引
# ### ... | notebooks/learn_numpy.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | week6_outro/bandits.ipynb |
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import tensorflow as tf
import numpy as np
#for slici... | dataset_tutorial.ipynb |
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import random
# +
numbers = [1,2,3,4,5,6,7,8,9]
squa... | Demos/Loops/While_Loop_Demos.ipynb |
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# # Exercise 5.05: K-NN Classification
import pandas ... | Chapter05/Exercise5.05/Exercise5.05.ipynb |
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import numpy as np
import numpy.linalg as npl
trainse... | notebooks/recursive_least_sqaures.ipynb |
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import p... | notebooks/graph_algos/attrib2vec/corpus 2020 audience_overlap lvl data 3.ipynb |
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# ## Configuration for Colab
# +
import sys
IN_COLAB = "go... | 03.DDPG.ipynb |
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# %matplotlib inline
#
#
# Creating MNE's data struct... | stable/_downloads/f51d54a1c1f3584f45318492102672d3/plot_creating_data_structures.ipynb |
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# # Gensim - Doc2vec untuk Similarity Content
# Simila... | 3_Gensim_Doc2vec_Similarity_Content.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
fr... | DepthSlicing.ipynb |
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# # MadMiner particle physics ... | examples/tutorial_particle_physics/2a_parton_level_analysis.ipynb |
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# # Differential UWB model
#
# The ideas behind this m... | uwb-beacon-firmware/doc/report/models/Differential 2 beacons.ipynb |
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# + [markdown] id="rpZiUllIKheS"
# 0. Imports
# + id="4RzJ03PpKVsC"
import p... | spravanie_zamestnancov_v_zavislosti_od_casu_II/ZAM_logits_estimate.ipynb |
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import numpy as np
# import tensorflow.keras as ke... | emoji_net/pix2pix_emoji.ipynb |
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from utils import *
from azur... | chapter04/Registered_tabular_dataset.ipynb |
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# + [markdown] id="view-in-github" colab_type="... | Course3-Probabilistic_Deep_Learning_with_Tensorflow2/week4_KL_divergence.ipynb |
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# **Choropleth**
This notebook demonstrates a choropleth, a themati... | scenarios/Choropleth.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | colab/03_types_conversion.ipynb |
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import django, sys, os
sys.path.append('/home/max/software/... | literature_identification/induce_query.ipynb |
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# # Exercice 2 - Algorithme de Shor
# ## Contexte hist... | content/ex2/ex2-fr.ipynb |
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# # lab 1
# ## demo of print
print ("hello world")
1... | My First Notebook.ipynb |
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# ## 截断 & 考虑用户频率
#
# 此代码目对应解决方案中对于similarity的改进
#
# Th... | Semi-Finals/underline_trainning/Step1 itemCF_based_on_Apriori/6_Sta_for_SparseMatrix.ipynb |
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# # Exercise 2
# * Due: 21.11. at noon
# * Max points:... | Exercise 2.ipynb |
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# # HW3: Part 2 - GPUs
#
# v1.0 (2021 Spring): <NAME>,... | static/homeworks/physcat_sp21_hw3_p2.ipynb |
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import json
import os
import numpy as np
import tensor... | Generate GPT-2.ipynb |
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##### from __future__ import division
from re impo... | notebooks/accuracies_plot_reduced_vecs.ipynb |
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# ## Using submodel loss of active materials in PyBaMM... | examples/notebooks/submodel_loss_of_active_materials.ipynb |
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# # Getting Started with Data Augmentation
# ## Befor... | docs/notebooks/getting-started-with-data-augmentation.ipynb |
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# ## WHO Coronavirus disease (COVID-2019) 24 hour repo... | notebooks/WHO_DAILY_REPORT.ipynb |
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# + [markdown] slides... | code/04.PythonCrawlerGovernmentReport.ipynb |
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# # A5 Extension Plan
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im... | 00_LoadData.ipynb |
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# %matplotlib inline
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# Audio Feature Augmentation
#... | docs/_downloads/c7aabc084299906190044ec9d37b7d0e/audio_feature_augmentation_tutorial.ipynb |
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from kirby.experiment import Experiment
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# **Authors:**
#
# <NAME> - 500513 - <EMAIL>
# ... | notebooks/Homework 8.ipynb |
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# # clean dataset
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#Needed Modules
import numpy as np
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# # Experiment 1.3 XGBoost with class balancing
#
# Tr... | notebooks/tith_reasmey-10845345-week2_xgb_class_balance.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 20202/pcd_20202_0902_conway.ipynb |
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# # Creating pandapipes Networks
# This tutorial will... | tutorials/Creating a simple network.ipynb |
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import keras
dir(keras)
# ### Keras Basic
# #### Mo... | keras/Keras.ipynb |
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# # 第4章 方差掉期：复制的一课
#
# 本章的通过期权复制方差掉期的损益的方法相当有技巧性，还展示了离... | volatility-smile/.ipynb_checkpoints/chapter-4-checkpoint.ipynb |
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# ## Part I: Decision trees
#
#
# Here, we will use de... | Exercise8_DT_NN.ipynb |
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# ## Abstract
# - Utiliser un réseau RNN pour prédire... | III - OUTIL_BOURSE.ipynb |
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# # Bubble Charts: An in-class challenge
#
# A bubble chart is a scatter... | Assignments/12_BubbleCharts/BubbleCharts.ipynb |
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# # Typeform Data API Test
# ทดสอบกา... | docs/typeform-data-api-test.ipynb |
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import os
os.environ["CUDA_DEVICE_ORDER"] = "PCI_B... | ImageCaptioning_Flickr8K/ImageCaptioning_Flickr8K.ipynb |
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# # Fibonnaci Sequence
#
# In this interview excercise... | code/algorithms/course_udemy_1/Recursion/Recursion Interview Problems/Recursion Problems - PRACTICE/Recursion Problem 3 - Fibonacci Sequence.ipynb |
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# # Einführung in Machine Learning - Schnelldurchgang
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# # 10장. 특성 선택을 사용한 차원 축소
# 이 노트북을 주피터 노트북 뷰어(nbviewe... | 10.ipynb |
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# # Singular Value Decomposition (SVD) Tutorial
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# # Monetary Economics: Chapter 4
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# _This notebook contains code and comments from Secti... | ensemble-methods-notebooks-master/Ch5.1-gradient-descent-for-minimization.ipynb |
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