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# # Defining ground truth
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# standard
... | code/01_generate_ground_truth.ipynb |
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import napari
from skimage.io import imrea... | docs/demo.ipynb |
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# # Importing packages
from pyLMS import *
import mat... | Example.ipynb |
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import numpy as np
from keras.models import Mo... | notebooks/layers/embedding/Embedding.ipynb |
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# # Tiling imagery and labels using the `solaris` Pytho... | docs/tutorials/notebooks/api_tiling_tutorial.ipynb |
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# # Example of Logistic regression
#... | 01-Regression/LogisticRegression.ipynb |
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# + [markdown] nbpresent={"id": "62... | Population_Segmentation/Pop_Segmentation_Solution.ipynb |
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#import jax.numpy as np
#from jax import pmap
impo... | Test tensor completion.ipynb |
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# # Introduction to Linear Algebra
#
# This is a tutor... | tutorials/LinearAlgebra/LinearAlgebra.ipynb |
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# # Notebook for Predictin... | notebooks/Extract_SPECTROGRAMS.ipynb |
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# # Results 2 - Powercell - More Capacity
#
# * Result... | notebooks/results_4_powercell.ipynb |
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import tree.ctutils as ctu
from tree import treeut... | scripts/notebooks/halo/Merger_property_plot.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | module2-loadingdata/LS_DS_112_Loading_Data.ipynb |
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# # Top Movies Data Processing
#
# This notebook conta... | filmordigital/top_movies_data_processing.ipynb |
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# + id="rRv0FICB8DZi" executionInfo={"status": "ok", "... | tensorflow/day3/answer/A_03_05_sonar_retrain.ipynb |
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# # rank
# ## same
# +
from my_happy_graphviz import... | examples/0800_0101_rank.ipynb |
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from keras.layers import Input, Conv2D, Lambda, me... | SiameseNet.ipynb |
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# # Setup
# +
import sys
import os
import re
import ... | deep_models/paper_06_mvcnn/models.ipynb |
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# # 離群值處理
# #### Detect
# +
import numpy as np
impo... | .ipynb_checkpoints/mod04-checkpoint.ipynb |
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# # Passing a function as an argument to another funct... | Functional_Thinking/Lab/26A-High_Order_Function.ipynb |
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# ## Readme
#
# ---
#
# **Advanced Lane Finding Projec... | .ipynb_checkpoints/Writeup-checkpoint.ipynb |
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# + [markdown] id="-pNWScUokvZ8"
# # Challenge: Analizando títulos de Netflix... | 0. Herramientas para la Ciencia de Datos/5. Intro a SQL/Challenge.ipynb |
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# # Taylor problem 5.50
#
# last revised: 21-Jan-201... | 2020_week_2/Taylor_problem_5.50_CDLCopy.ipynb |
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# # Implementing Adaline Model
import numpy as np
imp... | Adaline.ipynb |
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import numpy as np
# from tempfile import ... | models/TraditionalModels_OnlyMFCCs.ipynb |
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# # Pretrained GPT2 Model Deployment Example
#
# In this noteboo... | examples/triton_gpt2/GPT2-ONNX-Azure.ipynb |
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# + [markdown] run_control={"marked": true}
# # Introd... | week1/Week1_Introduction_to_Machine_Learning_and_Toolkit_HW.ipynb |
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# get_ipython().magic('matplotlib notebook... | templates_notebooks/template_zmeantransect_clim.ipynb |
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from sigelmsync import sigelmsync
from starkelmsync im... | ELM_cycles.ipynb |
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# Installing necessary libraries with pip
# !pip insta... | Ch05/Chapter05.ipynb |
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# # `gollum` Quickstart
# %config InlineBackend.figur... | docs/quickstart.ipynb |
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# # Welcome to fastai
# >... | nbs/index.ipynb |
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# # Sea surface temperature
#
# This is an example of ... | notebooks/Dfs2 - Sea surface temperature.ipynb |
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# # Naive Bayes classifier
# +
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from os.pat... | notebooks/classifiers_02_simple_classifiers.ipynb |
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# # Use Keras and hyperparameter optimization (HPO) to... | cloud/notebooks/python_sdk/experiments/deep_learning/Use Keras and HPO to recognize hand-written digits.ipynb |
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# # Load packages
import numpy as np
import pandas as... | 04 Create data for 2019 prediction.ipynb |
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# data analysis and wrangling
import pandas as pd
... | notebooks/ParquetCleanNetworkDetails.ipynb |
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# #!/usr/bin/python
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import matplotlib.pyplot as pl... | notebooks/predicting_financial_market_returns-2000-2017-(monthly).ipynb |
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# # Section 4 - Computer vision-based machine ... | Analysis.ipynb |
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import pandas as pd
import numpy as np
import matplotl... | Plotting/Test Plots.ipynb |
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] activate .
# # Futamura... | examples/futamura/futamura.ipynb |
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# # jupyter 사용방법
#
# 실행은 block 별로 된다!! 그래서 하나하나 끊어서 할 ... | src/recommendation/data_analysis/how_to_read_data.ipynb |
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# + [markdown] id="QB7BF7_SZeiW" colab_type="text"
# [Open with Colab](https:... | learn_generative_model.ipynb |
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# # What is pro... | notebooks/01a-instructor-probability-simulation.ipynb |
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line = '– <NAME>: I’m The Song That My Ene... | Playfield.ipynb |
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# ## Omega and Xi
#
# To implement Graph SLAM, a matri... | 2. Omega and Xi, Constraints.ipynb |
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# # Classification of text doc... | Part 7 - Natural Language Processing/document_classification_20newsgroups.ipynb |
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# > **How to run this notebook (command-line)?**
# 1. ... | notebooks/Lib-INVENT_RL1_QSAR.ipynb |
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# This notebook demonstrates the pipeline for using th... | examples/Pipeline_03_Linear_Method.ipynb |
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# <small><small><i>
# All the IPython Notebooks in thi... | 002_Python_Functions_Built_in/028_Python_hasattr().ipynb |
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torch.cuda.is_available()
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from tqdm ... | get_attn_dists.ipynb |
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# ### Task 8: Largest product in a series
# As always... | python/Problem8.ipynb |
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# ## To make the librar... | nexon/rzt.ai.notebook-40.ipynb |
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# %matplotlib inline
#
# # 2D Optimal transport for d... | _downloads/76a784f1b4907a99f6b908d9a32104cc/plot_OT_L1_vs_L2.ipynb |
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# Run this notebook before anything else!
import os
i... | Notebooks/DownloadHiRISE/DownloadHiRISE.ipynb |
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# + id="kkRdSCnY3Vul"
import pandas as pd
import numpy as np
# + id="AmAh_Ou... | filmweb_base_classifier.ipynb |
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# + id="MHNr1zXp4diG" executionInfo={"status": "ok", "timestamp": 16283275095... | _docs/nbs/recsys-gym-simulation.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Regresion_y_evaluacion_de_hipotesis.ipynb |
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# # The Redistribution Function
#
# **<NAME>**
#
# **J... | docs/redistribution.ipynb |
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import os
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# + [markdown] colab_type="text" id="TBFXQGKYUc4X"
# ##### Copyright 2018 The... | site/en/tutorials/images/classification.ipynb |
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# + pycharm={"is_executing": false}
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import os
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# # CNTK 599A: Sequ... | Tutorials/CNTK_599A_Sequence_To_Sequence.ipynb |
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import torch
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import torch.nn... | 2 - LeNet-5 MNIST.ipynb |
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import numpy as np
import sta... | mplot_example.ipynb |
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# # Exercise 4 - Random vector
# **The content o... | support_files/en/.ipynb_checkpoints/T6_random_vector-checkpoint.ipynb |
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import numpy as np
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import seaborn as sns
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import pandas... | Seaborn.ipynb |
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# # Demo 1: Spreadsheets
#
# ## USAspending
# [![USAsp... | demos/01-Spreadsheets.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# + [markdown] nbgrader={"grade": false, "grade_id": "jup... | nbgrader/tests/apps/files/test.ipynb |
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# # Use Python function to recognize hand-written digi... | cpd4.0/notebooks/python_sdk/deployments/python_function/Use function to recognize hand-written digits.ipynb |
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# #%matplotlib notebook
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from m... | drafts/Animation.ipynb |
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# # <NAME>'s First Ascend to Everest
... | application/physical/notebooks/MrJornetEverest.ipynb |
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# %matplotlib inline
from __future__ import divisi... | FCI/fmri-processing-scripts/identify_bad_fci_blocks.ipynb |
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# # array 对象
#
# 2.1 ndarray 对象
# 2.1.1 创建 array... | develop_language/python/doc/science_compute/ipynb_files/chapter2.ipynb |
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# default_exp core
# -
# # Core
#
# > API details... | 00_core.ipynb |
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# # DataFrames
#
# DataFrames are the workhorse of pan... | Day3&4/Python-Part1/Pandas/DataFrames.ipynb |
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# Copyright (c) Microsoft Corporation. All rights r... | how-to-use-azureml/automated-machine-learning/forecasting-grouping/auto-ml-forecasting-grouping.ipynb |
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# + _cell_guid="bc0bc872-20c1-4f39-891c-e1ea6eeebf3a" ... | learntools/python/nbs/ch3-testing.ipynb |
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# ## Prism 是甚麼？
# 在[Prism 6 的首頁](http... | Shell-Prism6-Tutorial-1.ipynb |
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# # Building 1D Rydberg Crystals
# The following note... | tutorials/applications/Building 1D Rydberg Crystals.ipynb |
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# # EDA about companies creation
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# %run "../confi... | notebooks/eda/eda_companies_creation_in_france.ipynb |
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# + id="b4812c1b"
# ! git clone https://github.com/jon... | notebook.ipynb |
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# [source](../../api/alibi_detect.od.vaegmm.rst)
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samples = ["the cat sat on the... | one_hot encoding with hashing trick in numpy.ipynb |
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from perspective import PerspectiveWidget
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# Suppose we have a list of N numbers ... | PythonJupyterNotebooks/Week3-Day1-Challenge.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | main.ipynb |
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# # Navigation using Double DQN
#
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#
# In this no... | Project-1_Navigation/Navigation/02.Navigation-Double_DQN.ipynb |
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# # Testing Notebook 03
#
# This notebo... | testing_notebooks/jlehrer_testing_notebook_03.ipynb |