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# # illusionist: Float Widget Gallery
# #... | examples/widget-gallery-floats.ipynb |
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# # Introduction to pandas
#
# *I'd like to thank <NAM... | notebooks/pandas-intro.ipynb |
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#importing libraries
import numpy as np
import pandas ... | SVM Handwritten Digit Recog load_digits .ipynb |
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# ### 변수의 타입을 지정하는 것처럼 보이지만 실제로는 주석
# 따라서 변수의 타입이 무엇이 ... | 2017/Issue/The Fun of Reinvention/example.ipynb |
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import rlssm
import pandas as pd
import os
# #### Imp... | tests/notebooks/RLDDM_fitting.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Twitter_Sentiment_Analysis_and_Text_classification_project.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # A... | .ipynb_checkpoints/AI_KFBS_2017-checkpoint.ipynb |
# ##### Copyright 2020 The OR-Tools Authors.
# 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 ... | examples/notebook/examples/cover_rectangle_sat.ipynb |
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import numpy as np
from sklearn.datasets import make_m... | nn_from_scratch.ipynb |
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# # [Project Euler](https://ProjectEuler.net)
# [This ... | euler/Project Euler (Python 3) - to problem 100.ipynb |
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# # WWW: Will the Warriors Win?
#
# ## 18 April 2016
#... | pytudes/ipynb/WWW.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 23Octubre.ipynb |
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# + [markdown] id="kluNh_ePe-l3" colab_type="text"
# # **Gujarati Character R... | Character Recognition (CNN)/Gujarati_ML.ipynb |
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# # Introduction to Machine Learning - CSE 474/574
# ... | ML/Notebook/notebooks/Introduction.ipynb |
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# # Working with Datastores
#
# Al... | 04A - Working with Datastores.ipynb |
# # Benefits of using feature selection
#
# In this notebook, we aim at introducing the main benefits that can be
# gained when using feature selection.
#
# Indeed, the principal advantage of selecting features within a machine
# learning pipeline is to reduce the time to train this pipeline and its time
# to predict. ... | notebooks/feature_selection_introduction.ipynb |
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# + [markdown] id="8FLud1n-3pVm" colab_type="text"
# # XGBoost
# + [markdown... | Dataset/Udemy_Machine_Learning_A_Z/Part 10 - Model Selection _ Boosting/Section 49 - XGBoost/Python/xg_boost.ipynb |
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import tsfresh
import pandas as pd
import numpy as np
... | 20161110_random_data/create_features_random_data.ipynb |
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from pyspark.sql import SparkSessio... | a01_PySpark/e01_Resources/PySpark-and-MLlib/Linear_regression_ecommerce.ipynb |
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# + [markdown] deletable=true editable=true
# ![data-x... | 07b-tools-word2vec_add_missing_si/notebook-nlp-sentiment-analysis-imdb-afo_v1.ipynb |
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# +
# # !pip install graphviz
# -
# To produce the de... | notebooks/lab13_cluster_analysis.ipynb |
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# ## Evergreen data extraction and analysis
# This not... | src/third_party/wiredtiger/bench/analytics/custom_analysis/evergreen_analysis.ipynb |
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# ## Model Checkpoint to Save Weights
# You've now tra... | Keras_Callbacks/Model Checkpointing.ipynb |
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# Before you turn this problem in, make sure everythin... | student-notebooks/05.02-Refinement-Protocol.ipynb |
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# # Assignment 3 - Building a Custom Visualization
#
#... | Sample Oriented Task Driven Visualizations.ipynb |
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# + id="oMpVoOgFsZoe" colab_type="code" colab={}
from ... | Finetuning.ipynb |
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# # Matplotlib practice tasks
import numpy as np
impo... | Plotnikov_Grigory/matplotlib_practice_tasks.ipynb |
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# # 量子・古典ハイブリッドの量子機械学習アルゴリズムを使って、新しい素粒子現象の発見を目指す
# この... | source/jp/vqc_machine_learning.ipynb |
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import os
from tensorflow.keras import layers
fro... | CNNs/tranfer_learning.ipynb |
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# # Introduction to Seaborn
#
# Seaborn is a Python data ... | 05-Introduction to Data Visualization/04-Introduction to Seaborn.ipynb |
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import os
import h5py as hd
verbose=1
pannuke= h... | notebooks/save_subset_pannuke.ipynb |
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# # Think Bayes
#
# Copyright 2018 <NAME>
#
# MIT Lice... | examples/regress_mine.ipynb |
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# # Quantum states
# Useful for working examples and p... | Lab 2 - Quantum States - Blank.ipynb |
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# # Jupyter Notebook里显示图片
img_file = 'test.jpg'
# ##... | jupyter_notebook/jupyter_notebook_show_image.ipynb |
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import torch
vecs = []
vecs.append([0]*100)
with open... | Dummy_Notebook.ipynb |
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import numpy as np
import pandas as pd
import plotly.e... | Oren/06_Mapping_and_Playing.ipynb |
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import pandas as pd
import numpy as np
visit = pd.rea... | Data/Data Manipulation.ipynb |
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# # Más Pandas
# - Filtros
# - agregaciones y agrupac... | 02-02_a_python-intermedio.ipynb |
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# # Homework 9.2: MLE of microtubule catas... | _site/software/hw9.2.ipynb |
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# # Week 2
#
# ## Binary Classification
# *Example: S... | 01_neural-nets-and-dl/logreg-as-nnet.ipynb |
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# ### Assignment 3 - Sentiment Analysis
#
#... | notebooks/LA_Assignment3.ipynb |
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# 그래프, 수학 기능 추가
# Add graph and math features
impo... | 20_bisection.ipynb |
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# # Python - Time Series Data with Pandas
# +
from da... | nbs/01_pandas_time_series.ipynb |
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# # Substitute functions
# This notebook contains some... | src/extracode.ipynb |
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# ## 7.1: ファセットの活用
# +
# リスト 7.1.1 FacetGrid クラスによるグラ... | notebooks/7-01.ipynb |
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# # Lemmatization & Part-of-Speech Tagging... | modules/ai-codes/modules/preprocessing/lemmatization-post.ipynb |
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import numpy as np
import pandas as pd
df = pd.read_... | public/tree/resize_csv.ipynb |
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# # MNIST softmax
#
# * MNIST data를 가지고 softmax classi... | tf.version.1/02.regression/03.1.mnist.softmax.ipynb |
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import PyKDL as kdl
# %pylab inline
np.set_printoption... | python/ur10_kin_cal.ipynb |
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# # Training Many PyTorch Models Concurrently with Das... | examples/pytorch/02-pytorch-gpu-dask-multiple-models.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | Sentiment_Classification.ipynb |
# -*- coding: utf-8 -*-
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# # FMDataAPI Sample Results
#
# b... | Sample_results.ipynb |
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# language: python
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# ## Setup
from ... | analyses/seasonality_paper_st/fapar_only/shap_map_plot_peaks.ipynb |
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# # Tutorial on Image-based Experimental Modal Analysi... | Image Based Experimental Modal Analysis Tutorial.ipynb |
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from chembl_webresource_client.new_client import new_c... | notebooks/FETCH_SMILES.ipynb |
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def lisas_workbook(n,k,a):
num_special=0
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#########################K-Cross Fold Validation #... | Employee Performance Appraisal for Salary Hike/EmployeeSalarydatasetComparitiveAnalysisusingMl.ipynb |
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# <h1>Green Screen</h1>
# <p>The project demonstrates ... | green screen.ipynb |
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# # Spatial Declustering in Python for Engineers... | examples/Declus.ipynb |
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# # Import the Dependencies
import tensor... | Fake News Classification using LSTM and BiLSTM.ipynb |
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#functions for running storm data
def interpolate_... | subroutines/storm_masking_routines.ipynb |
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# # Results: Tiger Scaled
# <b> MIL </b> <i>stratifi... | results/.ipynb_checkpoints/Tiger_Results-checkpoint.ipynb |
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# %autosave 0
# # Dictionary and Set
#
# Dictionary a... | Python-4 Dictionary and Set.ipynb |
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# + id="QZhIwy1isa1F" colab_type="code" colab={"base_uri": "https://localhost... | examples/bwimcp.ipynb |
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import matplotlib.pyplot as plt
import numpy as np... | social-tags/notebooks/helper-scripts/plot-micro-f1-at-k.ipynb |
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from IPython.display import display
import mglearn
# ... | ML/intro_ML_05_model_evaluation_and_improvement.ipynb |
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# # StarAI - Prepro... | note/00-data-qry/starai-preprocess.ipynb |
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# # Exploring other sentiment analysis models
#
# ## A... | DataAnalysis/Notebooks/.ipynb_checkpoints/Sentiment analysis-checkpoint.ipynb |
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# # Conditioning of evaluating tan()
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# ## 1. Cosine recursion
#
# I implemented a (bugg... | set01/sci-comp-hw-1-stefan.ipynb |
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// -*- coding: utf-8 -*-
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// # ML.NET - D... | Notebooks/ML.Net - DataFrame-AutoML-Demo.ipynb |
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# # M... | Sessions/Session10/Day0/BriefIntroToMachineLearning.ipynb |
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# # Assignment 2018 - Fundamentals of Data Analysis
#... | Fundamentals of Data Analysis .ipynb |
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# ## Importing Relevant Libraries
#
import json
import time
import requests
import os
from azure.storage.blob import BlockBlobService
import ... | Manufacturing/automation/artifacts/notebooks/convert_pdf_to_json.ipynb |
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# Python for Everyone!<br/>[Oregon Curriculum Network]... | Permutations.ipynb |
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# ## Data Visualisation - Graded Questions
#
# `Note`... | 1. Python Introductory Course/4. Data Visualization/Data Visualisation - Graded Questions/Data Visualisation - Graded Questions.ipynb |
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from collections import Counter
class MyCounter(Co... | Day 21 Assignment.ipynb |
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import pandas as pd
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# # Analysing the Earnings and Women Participation in ... | Analysing the Earnings and Women Participation in Recent Graduates.ipynb |
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# # Lab 05: K-Mean Clustering
# ## Sklearn
# +
## dat... | Lab05/Lab05.ipynb |
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import torch
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# # Dog Breed Identification
# ## <NAME>
#
# ### tran... | Transfer_Learning_aug.ipynb |
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# ## Import Packages
# +
import sys
impo... | GEIGER Cloud Logic.ipynb |
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# # Halting problem
#
# - toc: false
# - badges: fals... | _notebooks/2020-08-07-halting-problem.ipynb |
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# pip install ForwardStepwiseFeatureSe... | FSFS examples/FSFS Reggresion Example.ipynb |
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# Load Extension for noTeXbook theme
# %load_ext notex... | 0_prelude/ml_data_model.ipynb |