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# # ECG Heartbeat Classification
# + pycharm={"name":... | code/run_all.ipynb |
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# # Overview: Game Maps
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# Pandas
import numpy as ... | jupyter/game-maps.ipynb |
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# ## Dependencies
# + _kg_hide-input=true
import json... | Model backlog/Train/31-jigsaw-train-1fold-xlm-roberta-large-optimized.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | marchantia_stress.ipynb |
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# # Setup
# +
import os
import scanpy as sc
import n... | notebooks/preprocessing-explore.ipynb |
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# # NLP 2 : Neural Embeddings, Text Classi... | S2/RITAL/TAL/TME/TME2/Dan.ipynb |
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# # Content personalization
# ## Without context
# This... | docs/examples/content-personalization.ipynb |
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# # 在一分钟内实现一个图形分类应用
#
# 在本教程中，我们会演示使用TinyM... | docs/zh_CN/source/quickstart/quickstart_in_one_minute.ipynb |
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# This is in how `data/mongo-novice-materials.json` wa... | get_source_data.ipynb |
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# # Convolutional Neural Network (CNN)
# loading libr... | apps/handwritten-digits-recognizer/notebooks/cnn.ipynb |
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# [FProfile.jl](https://github... | Manual.ipynb |
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# + [markdown] slideshow={"slide_type": "-"}
# ## Cour... | 05_inference/05_02_inference.ipynb |
# # In this notebook....
#
# Using HypnosPy, we first classified sleep using the most common heuristic algorithms, such as Cole-Kripke, Oakley, Sadeh, Sazonov and the Scripps Clinic algorithm.
#
# Once sleep was classified, we derived the well-established sleep metrics, such as arousal, awakening, sleep efficiency, tot... | mdpi_sensors/hypnospy_sleepmetrics_by_sleepwakealgs.ipynb |
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# ## Forecasting, updating datasets, and the "news"
#
... | examples/notebooks/statespace_news.ipynb |
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# # Introduzione a Tensorflow
#
# TensorFl... | tensorflow.ipynb |
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# # Notebook to try to get the CPI (Consumer Price Index) for... | notebooks/002-mt-getting-the-cpi-from-the-world-bank.ipynb |
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# # Saying the same thing multiple ways
# What happen... | ch09fileformats/11ControlledVocabularies.ipynb |
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import random
import numpy as np
from math import erfc... | brwnn-raise_res.ipynb |
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# # Assignment 2 - Bacterial Bomb
# +
# Packages
# %... | A2.ipynb |
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# + [markdown] tags=[]
# # Convolutional N... | demo.ipynb |
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# # Unsupervised outliers detection (mixture of data)
... | notebooks/old_set/new.ipynb |
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import glob
import os
import librosa
im... | Urban Sound Classification using CNN.ipynb |
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# # Python Debugger
#
# You've probably used a variety... | 4-assets/BOOKS/Jupyter-Notebooks/03-Python_Debugger_(pdb)-checkpoint.ipynb |
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# 最初に必要なライブラリを読み込みます。
# +
from sympy import *
from sy... | docs/20210120/quantum_computing_2_1-2_4.ipynb |
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# <img src="../../images/qiskit-heading.gif" alt="Note... | community/games/quantum_counterfeit_coin_problem.ipynb |
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# # Practical Session 2: Classification algorithms
#
#... | DSPNP_practical2/DSPNP_notebook2.ipynb |
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# # Pytorch Resnet to get image features then LSTM wit... | kgl/meyer/pytorch-resnet-lstm-with-attention.ipynb |
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import tensorflow as tf
import pandas as pd
import num... | Embedding CV LSTM/Model LSTM Embedding Dense Network.ipynb |
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# + [markdown] id="gZABpep_V-8C"
# # CUDA Exercise 04
# > Matrix summation ex... | Solution/Exercise_04.ipynb |
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# # Identify "cloudy transition" Spitzer exoplanet hos... | id.ipynb |
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path = "/../"
def simply(path):
stack = []
for... | Stack/Simplify path.ipynb |
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from sklearn.svm import OneClassSVM
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# # Streamlines tutorial
# In this tutorial you will l... | Examples/notebooks/Streamlines.ipynb |
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@info "Train baseline Single Headed Attention ... | notebooks/SHA-RNN.ipynb |
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import pandas as pd
from nltk.tokenize import Twe... | Untitled.ipynb |
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# default_exp card
# -
# # Card
#
# > API details... | 00_card.ipynb |
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# + [markdown] deletable=true editable=true
# # Public... | markdown_generator/publications.ipynb |
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# ### Installation
# - `pip install eleanor` ([eleanor... | notebooks/online_tess_science_eleanor.ipynb |
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# # Ex3 - Getting and Knowing your Data
#
#
# ### Ste... | week4/day2/exercises/01_Getting_&_Knowing_Your_Data/Occupation/Solutions.ipynb |
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# + colab={} colab_type="code" id="_I... | docs/tutorials/render_textured_meshes.ipynb |
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from tools import *
from models import *
import pl... | notebooks/Train_multi_model_DanQ.ipynb |
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from IPython.display import HTML
HTML('''... | hackathons/hackathon2/index.ipynb |
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import numpy as np
import pandas as pd
import os
f... | notebooks/SI/S01_effect_finite_replication_rate.ipynb |
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# + [markdown] papermill={"duration": 0.032216, "end_t... | Notebooks/RadarCOVID-Report/Daily/RadarCOVID-Report-2020-10-26.ipynb |
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import pickle
from knn import ProjectKNN
from xgmodel ... | projeto.ipynb |
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# ## Custom components
#
# As I mentioned earlier in t... | examples/07_Custom_Components.ipynb |
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# # jupyter notebook生成PDF文件采用LaTeX编译方式，须先行安装Tex软件。（Lin... | docs/IMPOART_NOTICE_FOR_CHINESE_PDF_DOCUMENT.ipynb |
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# **interval starts from 0**
#
# i.e. 0 is 0:00-3:59, ... | .ipynb_checkpoints/time2interval-checkpoint.ipynb |
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# For convenience, let's begin by enabling [automatic ... | tutorials/2 Front End User/2.4 QRenderer Introduction/QRenderer Introduction.ipynb |
# -*- coding: utf-8 -*-
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# <a id='orth-proj'></a>... | tools_and_techniques/orth_proj.ipynb |
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import numpy as np
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# + deletable=true editable=true
# %load_ext cython
... | 2_Curso/Laboratorio/SAGE-noteb/IPYNB/MISCE/122-MISCE-percolacion-numpy-cython.ipynb |
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# <a href="https://colab.research.google.co... | t81_558_class_03_5_weights.ipynb |
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# This notebook is designed to run in a IBM Watson Stu... | coursera_ml/a2_w3_kmeans_SparkML.ipynb |
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# # Demo - Fairness Analysis of COMPAS by ProPublica
#... | docs/notebooks/demo-compas-analysis.ipynb |
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# DataSet Example
# ==================
import qcodes ... | docs/examples/DataSetExample.ipynb |
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# ## 寻找最大间隔
# 分隔超平面的形式:$W^TX+b$
# 由点到直线距离公式:
# $$
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# ## The Battle of the Neighborhoods - Week 1
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# Copyright 2020 MONAI Consortium
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# ## Sampling Implementation of QGRNN in Pennylane
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# + [markdown] id="view-in-github" colab_type="text"
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# # Numpy
# ## working with arrays in Python
#
# ![](h... | numpy.ipynb |
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# + [markdown] id="ABs6xC-hWIjM"
# #Άσκηση 1 , Νευρωνικά Δίκτυα
# + [markdow... | Neural Networks/ex1_Supervised Learning - Classification/implementation_big_dataset.ipynb |
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# !python --version
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# # Implementation
# This section shows how the linea... | content/c2/code.ipynb |
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### ESOL predictor: GCNN, random train/validate/te... | models/GroundTruthEsolModel.ipynb |
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# # An example notebook
# A [Jupyter notebooks](http:... | example.ipynb |
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# # SciPy Optimize Module
#
#
# ## Module Contents
#
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# # Chapter 2 End-to-end Machine Learning project
#
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# # Optimización media-varianza
#
# <img style="float:... | Modulo3/Clase12_OptimizacionMediaVarianza.ipynb |
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# + id="1s6mjoaXjoSp" executionInfo={"status": "ok", "timestamp": 16408291712... | solution_notebooks/Computing GC Content.ipynb |
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# ## 5.12 稠密连接网络(DenseNet)
#
# > 1. **与ResNet的主要区别在于，D... | dl/dive-into-dl/chapter05-CNN/5.12_densenet.ipynb |
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# All content can be freely used and adapted under the... | notebooks/gravmetria/GRAV_somigliana_ar-livre_bouguer-v02.ipynb |
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# # Pydeck Earth Engine Introduction
#
# This is an in... | GetStarted/01_hello_world.ipynb |
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# ### Class Methods And Class variables
class Car:
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# # Balanced Network De-embedding
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# # Gaussian Blur, Medical Images
# ### Import resour... | 1_2_Convolutional_Filters_Edge_Detection/.ipynb_checkpoints/3. Gaussian Blur-checkpoint.ipynb |
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# + [markdown] tags=[]
# # Number of collisions
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