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# This is a toy example of using empirical c... | notebooks/survey_calibration_simulated.ipynb |
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# # Lab 01: Basic Python... | cs-master/cs401/Lab01-Basic Python_done.ipynb |
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# #!/usr/bin/env python
# -*- coding: utf-8 -*-
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# %matplotlib inline
#
# # Visualize channel over epo... | 0.12/_downloads/plot_channel_epochs_image.ipynb |
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# <i>Copyright (c) Microsoft Corporation. All rights res... | scenarios/similarity/01_training_and_evaluation_introduction.ipynb |
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pip install numpy
import numpy as np
import copy
# ![... | Basic Reinforcement Learning/.ipynb_checkpoints/BasicReinforcement-checkpoint.ipynb |
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# # Introduction to Methods Using Turtle
#
# Here we i... | turtle-draw-using-methods.ipynb |
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# Accession: https://www.ncbi.nlm.nih.gov/... | datasets/Norman_2019_curation.ipynb |
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# # Sampling of Dataset : 1250
import pandas as pd
d... | scripts/sampling_250_for_imbalance_testing.ipynb |
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# ### Bi-directional LSTM with average pooling
#
# Au... | experiments/bilstm_512_avg_pooling.ipynb |
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from kanren import run, fact, eq, Relation, var
... | artificial-intelligence-with-python-ja-master/Chapter 6/states.ipynb |
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... | Financial-Crime-Analysis/Challenge One.ipynb |
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# # Basic example
from quickdef import quickdef, quic... | experiments/quickdef/Example (python).ipynb |
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# # Final NLP project (University of Guilan)
# In this... | Project Final Solution.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="14W3B3KZJ7J_" outputId=... | src/install_dash_plotly_ngrok.ipynb |
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# This notebook was prepared by [<NAME>](https://githu... | graphs_trees/tree_lca/tree_lca_challenge.ipynb |
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import tensorflow as tf
import numpy as np
# -
... | day8/day8.ipynb |
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import numpy as np
import os
import matplotlib.pyp... | sequence models/notebooks/future_segmentation_generate.ipynb |
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# Note: This notebook about 40 MB of embedded output d... | .ipynb_checkpoints/Beat and Onset Analysis-checkpoint.ipynb |
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# # <center/>同步训练和验证模型体验
# ## 概述
# 在面... | tutorials/notebook/mindspore_evaluate_the_model_during_training.ipynb |
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"<NAME>"
greeting = "Hello World" # this is a string ... | session-4/scripts/1_Intro_to_Python.ipynb |
# +
#@title Copyright 2021 The Earth Engine Community Authors { display-mode: "form" }
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unle... | guides/ipynb/image_math.ipynb |
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# # Statistics essentials
#
# - hide: false
# - toc: true
# -... | content/post/basic-stats/.ipynb_checkpoints/basic-stats-checkpoint.ipynb |
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# # Surrogate model
#
#
# The objective of this work i... | README.ipynb |
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# ## DataFrame
# A DataFrame represents a rectangular ... | Python/Pandas/data_frames.ipynb |
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# # Day 2: Pearson Correlation Coefficient vs. Lead Time
#... | notebooks/subgroup3/04_CorrelationLeadTime.ipynb |
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# %matplotlib inline
import yt
import numpy as np
impo... | notebooks/Untitled.ipynb |
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# <!--NAVIGATION-->
# < [Jupyter Widg... | notebooks/01.00-overview.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
fro... | code/notebooks/bsnip001-Copy2.ipynb |
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# %matplotlib inline
import xarray as xr
from os.... | notebooks/templates/sam-run.ipynb |
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# # AI-Frameworks
# <center>
# <a href="http://www.in... | RecomendationSystem/3-Python-Neural-MovieLens.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | googlesheet.ipynb |
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# ## Create a NLP Pipeline to 'Clean' Reviews Data
# -... | .ipynb_checkpoints/NLP - Pipeline-checkpoint.ipynb |
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# %matplotlib inline
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from ... | Test/test.ipynb |
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# <h2 style="color:blue" align="center"> Missing Value... | 10_Missing_Values/2_Imputation_Sklearn/3_KNN_Imputer/KNN_Imputer.ipynb |
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include("asinclude.jl")
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## Demo
asinclude.@a... | asincludetest.ipynb |
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import sys, collections, functools, itertools, heapq, ... | IPython-notebooks/python_linear_data_structure.ipynb |
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# # Introduction to Data Science - Lecture 2 - Version... | 02-basic-python/lecture-02-version-control.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Amazon_130_Leetcode.ipynb |
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##https://towardsdatascience.com/simple-and-multip... | code/linear_model.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/balance_group_sat.ipynb |
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# + active=""
# 说明：
# 给定树的前序和中序遍历，构造二叉树。
#
# 注意：
#... | Tree/0829/105. Construct Binary Tree from Preorder and Inorder Traversal.ipynb |
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# # Tutorial - Plotting F' and F'' Schematas
# This tu... | tutorials/Canalization - BioModels - Schematas.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | module2-regression-2/Lecture_2_notes.ipynb |
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# # Training a Model on Encrypted Data
# +... | pycon-workshop-2020/2 - Training a Model on Encrypted Data.ipynb |
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# <a href="https://colab... | compute_affine_transform.ipynb |
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# # SLSTR spatial plotting, quality control and data i... | SLSTR/21_SLSTR_spatial_interrogation.ipynb |
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# ## The great 1 dimensional bandstructure function
# ... | 1D/User_interface.ipynb |
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matrix1 = [[5, 1, 6], ... | MyExamples.ipynb |
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# %reload_ext autoreload
# %autoreload 2
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import numpy as np
import re
#laa... | Dag4.ipynb |
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# <a href="https://colab... | notebook/Modeling_ICG_svr.ipynb |
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# # Adversarial Robustness Toolbox (ART) and scikit-le... | notebooks/classifier_scikitlearn_pipeline_pca_cv_svc.ipynb |
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# + jupyter={"outputs_hidden": false} pycharm={"name":... | Draw_figures_SQ.ipynb |
# -*- coding: utf-8 -*-
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# # Table tennis simulatio... | notebooks/tabletennis.ipynb |
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# # MEGI001-2101033 Introduction to Earth System Data
... | notebooks/task_6/florent-ralph_task6.2.ipynb |
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# # Welcome to the Geonotebook
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# # How to *Merge $k$ sorted lists* (in Python 3)
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# # Principal Component Analysis(PCA)
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# + [markdown] id="axF7OBsg-AJs"
# #Transformer
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# # Adding colors
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import pandas as pd
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# %% [markdown]
# # Imports
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# Importing all requir... | im/kibot/notebooks/kibot_volume_statistics.ipynb |
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from core... | dataset.ipynb |
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# The following functi... | COLLAB_Example.ipynb |
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# # Export an ImageCollection to Google Drive
import ... | notebooks/batch/ImageCollectionToDrive.ipynb |
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# # Question answering with TensorFlow
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# # PRMT-1984 [HYPOTHESIS] The spread of EM... | notebooks/26-PRMT-1984--emis-emis-practice-level-behaviour.ipynb |
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# %pylab inline
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# + [markdown] id="kQRtLPG5YR3O"
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# + id="0Tz2J0Cf... | report/ActivityAssignment.ipynb |
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# # 0.0. IMPORTS
#Importar bibliotecas
import bs4
imp... | web_scraping.ipynb |
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# # Create Simulated Data Set from Kinetic Model
# Thi... | notebooks/Create Data Set.ipynb |
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# # Finetuning of the pretrained Japanese BERT model
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# * [data.karta.orebro.se/](http://data.karta.orebro.s... | Öppen data orebro.se.ipynb |
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# # Process DeepSea datset
#
# In this notebook, the D... | code/generate_data/task2_generate_invivo_dataset.ipynb |
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# # 03 - Prequential Expanding
# Quebra o conjunto or... | 03 - Prequential Expanding.ipynb |
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import pandas as pd
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f... | 3/.ipynb_checkpoints/models-checkpoint.ipynb |
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# # Aprendizaje basad... | Bloque 3 - Machine Learning/01_Supervisado/9-Ensemble/01_Ensemble_Modelos.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Sequential/Eng_Hindi_transliteration_attention_up.ipynb |
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# import the pymongo library - this is the Python ... | mflix-python/notebooks/your_first_read.ipynb |
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# # Flopy MODFLOW Boundary Conditions
#
# Flopy has a ... | examples/Notebooks/flopy3_modflow_boundaries.ipynb |
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# # Multiple basins
# This example demonstrates the power... | docs/source/examples/notebooks/multiple_basins.ipynb |
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data = pd.read_csv('water_pot... | Water Potability/water potability calssification.ipynb |
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# # Beyond Hello World, A ... | dlaicourse/Course 1 - Part 4 - Lesson 2 - Notebook.ipynb |
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# # A1: Data Curation
# ___
# ## Step 1: Data Acquisit... | hcds-a1-data-curation.ipynb |
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# # Loading an OBO ontology into a `networkx` graph
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# # Regression Modeling
# ## IMPORTS
from... | Python/regression_modeling.ipynb |
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# We observed that time scaling matters *a lot* in... | experiments/old/Timescaling/.ipynb_checkpoints/Analysis-checkpoint.ipynb |
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# # Network Models
#
# Probably the easiest kinds of s... | network_machine_learning_in_python/_build/jupyter_execute/representations/ch5/single-network-models.ipynb |
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# # Basic Model Training with TensorFlow 2.0
# ## Pro... | 3.1 Lab Basic Model Training with Tensorflow.ipynb |
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impor... | troubleshooting/csmc_stage.ipynb |