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import pandas as pd
import matplotlib.pyplot as plt
import seabor... | performance-analysis/article/mini-topo/pods-resources-OAI-vs-K8S-vs-Operator/CR_4.ipynb |
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import pickle
# +... | data_explore/.ipynb_checkpoints/tf-kdl-result_explore-checkpoint.ipynb |
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# # Exercise A — apply numba the brute-force prime sea... | numba-primes/solution.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# <di... | AudioPhase/AudioPhase.ipynb |
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# # Occupation
# ### Introduction:
#
# Sp... | 03_Grouping/Occupation/Exercise.ipynb |
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# # Tutorial 06: Setting spatially varying fields
#
# ... | docs/ipynb/06-tutorial-spatially-varying-field.ipynb |
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# + [markdown] tags=["header"]
# <table width="100%">
... | notebookToHtml/biosignalsnotebooks_html_publish/Categories_/Train_and_Classify/classification_game_orange.ipynb |
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# + [markdown] id="cx82H4OmEZVR" colab_type="text"
# # Análisis de datos y re... | analisis_datos/estudio_del_precio.ipynb |
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# ## Clustering
#
# Last class we studied document vec... | week-2/week-2-2-class-empty.ipynb |
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# + [markdown] id="7OGyhw9v31o1"
# # Gamma Distributions
# + id="iPOUzf2j0lN... | notebooks/book1/02/gamma_dist_plot.ipynb |
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import cv2
import numpy as np
from matplotlib import p... | src/Menu.ipynb |
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#ifndef VEHICLE_H
#define VEHICLE_H
#in... | behavior Planning/behavior_planner/vehicle.h.ipynb |
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# Text provided under a Creative Commons... | lessons/02_Step_2.ipynb |
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# import everything and define a test runner funct... | session4/complete/session4.ipynb |
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import numpy as np
import matplotlib.pyplot... | week1_intro/seminar_gym_interface.ipynb |
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# ## Dictionary Comprehensions
#
# Assim como o List C... | log-prog-python/Compreensao em dicio.ipynb |
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import tensorflow as tf
from tensorflow im... | 01_ML_basics_with_Keras/07. Tuning hyperparams with the Keras tuner.ipynb |
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# # <img style="float: left; padding-right: 10px; widt... | hw1/cs109b_hw1_jason.ipynb |
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# <a id="1"></a> <br>
# ## Step 1 : Reading and Unders... | 6_K_Means_Clustering.ipynb |
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# ### Recommendations with MovieTweetings: Getting to ... | lessons/Recommendations/1_Intro_to_Recommendations/.ipynb_checkpoints/1_Introduction to the Recommendation Data - Solution-checkpoint.ipynb |
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# + [markdown] id="0qesHlWDmzVS" colab_type="text"
# ## Imports
# + id="R2rm... | src/MLRanking.ipynb |
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x=input()
print(x)
x=input("enter your name")
x
x=... | input fn.ipynb |
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# <img src="https://maltem.com/wp-content/uploads/2020... | Notebook/Lesson-logistic-regression/starter-code.ipynb |
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# # Ray RLlib Multi-Armed Bandits - Exploration-Exploi... | ray-rllib/multi-armed-bandits/02-Exploration-vs-Exploitation-Strategies.ipynb |
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# # Exercise 3.2 Learning From Data
# + pycharm={"is_... | .ipynb_checkpoints/Exercise_3_2-checkpoint.ipynb |
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# + id="JVca8a6AQ_SI" colab_type="code" colab={}
import pandas as pd
import n... | prediction.ipynb |
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# Encode MNIST images as compressed vectors that c... | flux/test_flux_autoencoder.ipynb |
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# # Plots for documentation
import numpy as np
i... | docs/docs/control/assets/doc_plots.ipynb |
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# # Regresión Lineal con Python
#
# Su vecina es una a... | 02RegresionLineal/01RegresionLinealConPython.ipynb |
# -*- coding: utf-8 -*-
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using Plots, LaTeXStrings
... | chapters/03.AutoDiff/autodiff.ipynb |
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# + [markdown] papermill={} tags=[]
# <img width="10%"... | Google Sheets/Gsheets_Send_data.ipynb |
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# + id="copyright"
# Copyright 2021 Google LLC
#
# Licensed under the Apache ... | notebooks/community/sdk/sdk_automl_image_object_detection_online_export_edge.ipynb |
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import numpy as np
# ## DataTypes & Attri... | introduction-to-numpy.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Python_Exercise_2.ipynb |
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# # Spectral Embedding Methods
# One of the primary e... | network_machine_learning_in_python/representations/ch6/spectral-embedding.ipynb |
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# + [markdown] id="WBk0ZDWY-ff8"
# <table align="cente... | Part1_TensorFlow.ipynb |
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import numpy as np
import pandas as pd
from sklearn.cl... | 6-c.ipynb |
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# # Building first level models using _nipype_ and _SP... | archive/first_level.ipynb |
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import numpy as np
import pandas as pd
import seab... | Kddcup99_Dataset-OneClass.ipynb |
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... | zarrification/zarrification_lens2_process.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # E... | explorando-dados-com-pandas.ipynb |
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import nltk
nltk.download(['punkt', 'w... | notebooks/Untitled.ipynb |
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# Example-2-GP-BS-Derivatives
# Author: <NAME>
# V... | Chapter3-GPs/.ipynb_checkpoints/Example-2-GP-BS-Derivatives-checkpoint.ipynb |
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# + [markdown] colab_type="text" id="Umer7W0VbITT"
# ## Setup Colab
# + cola... | models/hific/colab.ipynb |
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import numpy as np
import pprint
import sys
if "../" n... | DP/Value Iteration Solution.ipynb |
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# %load_ext autoreload
# %autoreload 2
# %env CUDA_VIS... | notebooks/00.1-data-exploration/crabeater_seal/0.0-Crabeater-seal-vocalization-exploration.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Lecture10.ipynb |
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# ## Configurations for Colab
# +
import sys
IN_COLAB... | 04.dueling.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | notebooks/05-label-propagation-for-node-classification.ipynb |
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# name: python3710jvsc74a57bd0a99ace1d12d52a1bbe3d6f19578e1877f6a52f23b84e79f24ee865afab... | notebooks/Reinforcement_Learning.ipynb |
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from rsna_retro.imports import *
from rsna_retro.metad... | 02_train_experiments/02_train_01_full.ipynb |
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# <center><em>... | 14.7 Resampling and Frequency Conversion.ipynb |
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from straw import straw
help(straw)
result = straw... | python/straw_notebook.ipynb |
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# Erasmus+ ICCT project (2018-1-SI01-KA203-047081)... | ICCT_it/examples/04/SS-07-Dalle_equazioni_differenziali_allo_spazio_di_stato.ipynb |
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# A. Using the **same Amazon product dataset from HW1*... | solutions/HW2 (Instructor Solution).ipynb |
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# + [markdown] id="BWgZD6aDxeh_"
# # Imports
# + cola... | fast_growing_comp.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | PyTorch_cifar10_tutorial_ROB313_2020.ipynb |
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# # SQLAlchemy Joins
# ## Setup
# Python SQL toolkit... | Joins.ipynb |
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# This notebook was prepared by [<NAME>](https://githu... | graphs_trees/graph_path_exists/path_exists_challenge.ipynb |
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# %load_ext autoreload
# %autoreload 2
from colle... | notebooks/paleo data.ipynb |
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# # Preparing a state with antiferromagnetic order in ... | tutorials/applications/Preparing state with antiferromagnetic order in the Ising model.ipynb |
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# # Ideas
# - more generalizable version of _apply so ... | notebooks/scratch_chainable.ipynb |
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# # Machine Learning: Intermediate report
#
# *Write y... | assignment/(YourID)_report2.ipynb |
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# # Tree LSTM modeling for semantic relatedness
#
# Ju... | chapter09_natural-language-processing/tree-lstm.ipynb |
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# ## Train classifier by layers
#
# This notebook trai... | notebooks/2. Train classifier (best of two)/2. Train classifier by layers [utterance level][60t].ipynb |
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import numpy as np
import pandas as pd
provider = pd.... | Cleaning_and_Merging/Cleaning 2017 Provider Data.ipynb |
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import cv2
import numpy as np
import matplotlib.pyplot... | all final/Dilation and Erosion.ipynb |
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# + [markdown] colab_type="text" id="77gENRVX40S7"
# ##### Copyright 2019 The... | site/en/tutorials/images/transfer_learning.ipynb |
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import numpy as np
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import matplotl... | Notebooks/machine_learning/optimization/knn_classifer.ipynb |
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from inspect import ... | notebooks/06_training_and_evaluating_model.ipynb |
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# # Mein erstes Jupyter Notebook
# ## Browser Kompati... | index_v2.ipynb |
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import numpy as np
import pandas as pd
pd.set_opt... | EDA.ipynb |
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from sklearn.model_selection import train_test_split
i... | Model/3-NeuralNetwork6.ipynb |
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# # SSIM
# +
import numpy as np
import matplotlib.pyp... | Example_and_Record/ablation_experiment/Img_Similarity.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | module3-make-explanatory-visualizations/LS_DS_123_Make_Explanatory_Visualizations_Assignment.ipynb |
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# + [markdown] colab_type="text" id="g_nWetWWd_ns"
# ##### Copyright 2019 The... | site/en/r2/tutorials/keras/save_and_restore_models.ipynb |
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#source: https://www.kaggle.com/philculliton/nlp-getti... | experimental/NLP_Tutorial.ipynb |
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# + [markdown] pycharm={"name": "#%% md\n"}
# # Object... | howto/2_detection/generate_tfrecords.ipynb |
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# # String Formatting
# ## Anatomy of Strings
# - Si... | book/python/01-string_formatting.ipynb |
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# + id="JSjG64ra4aFu" outputId="b24eeca0-6414-4d1f-de5... | 8_train_begining_layers_vs_end_layers/CIFAR10/CIFAR10_last4layer_fixed_cnn8layer.ipynb |
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# <br />
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#... | ResourceWatch/data_management/3) MODIS.ipynb |
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# <a href="https://qworld.net" target="_bl... | math/Math20_Vectors.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Notebooks/Ensemble.ipynb |
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import numpy as np
impo... | pyth/ens002.ipynb |
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# # Data and cleaning
# +
import pandas as pd
data =... | Toronto-neighborhood-clustering.ipynb |
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# ## Лабораторная работа №4
# ## CCN для задачи класси... | Lab_3_CNN_CIFAR_10_ZIADE (2).ipynb |
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# ## 第14讲 在数轴上标记不同的数
# + [markdown] heading_collapsed... | source/2021/500Answer/content/014_locate_points_answer.ipynb |
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# ## _*VQE; using its callback to monitor optimization... | aqua/vqe_convergence.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# ___
#
# <a href='http://www.pieriandata.com'><img sr... | 08-Time-Methods.ipynb |
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# # Model 1
#
# Four-layer deep network based on initi... | cnn/compare_models/model1.ipynb |
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# Importing Packages
#Scikit-Learn
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# # Solution for JSON Structured Data
#
# ---
# #### ... | lab/part_ii_json/json_solution.ipynb |
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#export
from local.torch_basics import *
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#
# # ggplot style sheet
#
#
# T... | matplotlib/gallery_jupyter/style_sheets/ggplot.ipynb |
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# + [markdown] deletable=false editable=false
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# # 実験を実行する
#
# Azure Machine Lear... | 04 - Run Experiments.ipynb |
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# # Multiple Movements
#
# Let's see how our robot res... | 07_Object_Tracking_Localisation/4_2_Robot_Localization/8_1. Multiple Movements.ipynb |
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# # Synthe... | docs/notebooks/prog_synthesis.ipynb |