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#
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# ## Cleaning the dataset
import ge... | Sales_Analysis_2/Cleaning_Store_Dataset.ipynb |
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# <img src="https://raw.githubusercontent.com/melipass... | lab-6-perceptron.ipynb |
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# # Find the best adversary
#
# - the idea is to train... | train_adversary.ipynb |
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# cd ..
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import numpy as np
impo... | exp-visgeno-rel/build_visgeno_imdb.ipynb |
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# + [markdown] button=false new_sheet=true... | docs/notebooks/Grammars.ipynb |
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# + [markdown] nbgrader={}
# # Project Euler: Problem ... | assignments/assignment01/ProjectEuler1.ipynb |
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# In this last part of the dissertation, we will price... | MSc Dissertation-UCL.ipynb |
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# # [Assignment #2: NPFL067 Statistical NLP II](http:/... | charles-university/statistical-nlp/assignment-2/kondrad.assign2/nlp-assignment-2.ipynb |
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# ## Automated Snow Leopard Detection with Mic... | notebooks/samples/ModelInterpretation - Snow Leopard Detection.ipynb |
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# # Tensor images
# This notebook gives an overview of... | examples/python/tensor_images.ipynb |
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# importing the required modules
import requests
from ... | Project01/Link_ETL/extract_url_korean.ipynb |
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# Copyright 2020 Google Inc. All Rights Reserved.
... | model_serving/caip-triton/direct-server/triton-simple-setup-sdk.ipynb |
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# + id="ur8xi4C7S06n"
# Copyright 2022 Google LLC
#
# Licensed under the Apac... | notebooks/official/ml_metadata/sdk-metric-parameter-tracking-for-custom-jobs.ipynb |
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# Import dependencies and file
# The dataset was obtai... | .ipynb_checkpoints/Data_Preparation-checkpoint.ipynb |
# ### Creating multi-panel plots using `facets`.
#
# #### Problem
#
# You want to see more aspects of your data and it's not practcal to use the regular `aesthetics` approach for that.
#
# #### Solution - `facets`
#
# You can add one or more new dimentions to your plot using `faceting`.
#
# This approach allows you to ... | docs/examples/jupyter-notebooks/facets.ipynb |
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# +
import requests
from bs4 import BeautifulSoup... | Collect Movie Data.ipynb |
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# + [markdown] id="fTFj8ft5dlbS"
# ##### Copyright 2018 The TensorFlow Author... | site/en/tutorials/keras/overfit_and_underfit.ipynb |
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# # Binary classification
# --------------... | docs_sources/examples/binary_classification.ipynb |
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def times2(var):
return var*2
times2(5)
# # map()... | python/python_part4.ipynb |
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# name: python37464bitbaseconda1aa5cdf7d7054ec... | WINE_SELECTION_DROP_NA_VALUES.ipynb |
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matrix = [[0,1,2],[3,4,5],[6,7,8]]
for row in range(le... | leetcodes/tstcodes.ipynb |
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# + [markdown] id="vEO2FZbVMl4O"
# # Purpose
# This notebook is used to map n... | members/omar/Mapping_Network_TCN.ipynb |
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# # Relationships in Data pt.1
# ## Variance
# Measu... | Class 2.ipynb |
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# # Part 3 Twitter Data Analysis
# ## Installing and importing R packag... | part3 - Flu twitter data exploration/Part3.ipynb |
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# # Benchmarking cell2location pyro model ... | notebooks/scvi_amortised/cell2location_synthetic_data_scVI_amortised_10x_data_batch_1250_2500_dropout_rate01_n_hidden128.ipynb |
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# # Fig 2C-I : Drug response... | figure_2/2C-I_PDX_predictions.ipynb |
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# <center>
# <img src="https://cf-cour... | House_Sales_in_King_Count_USA (1) (2).ipynb |
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# <h3>Simulación matemática 2018 </h3>
# <div style="b... | Modulo1/Clase6_AjusteCurvas.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # Fo... | 08_bundles_ex2.ipynb |
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# ### Let's draw a bar chart
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import numpy as np
i... | notebooks/Bar chart.ipynb |
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from collections import defaultdict
import matplo... | mobius_data_augmentation/notebooks/M-admissable-focused.ipynb |
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# # Omniglot symbol drawing speed exploration
# This ... | Chapter2/Symbol Drawing Speed.ipynb |
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# # Face Operation Project
# * This is a simple `open-... | beginner/Face-Operation-1-Open-CV-Py/.ipynb_checkpoints/ghost-image-checkpoint.ipynb |
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import pandas as p... | nb_data_analysis/covid_rec_pattern_example.ipynb |
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# + [markdown] id="st0Rer20lXyu"
# # TP 2 : Computer V... | motion_estimation_for_students.ipynb |
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# + [markdown] id="XBa81egYhqvT"
# **Mount Google Drive**
# + colab={"base_u... | MLPClassifier(Final).ipynb |
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# # Nibabel
#
# Nibabel is a low-level Python library ... | notebooks/03_nibabel_and_nilearn.ipynb |
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from IPython.core.interactiveshell import InteractiveS... | note_books/Basic.ipynb |
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from __future__ import annotations
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# # Lesson 1 Exercise 1: Creating a Table with Postgre... | L1_Introduction to Data Modeling /L1_Exercise_1_Solution_Creating_a_Table_with_Postgres.ipynb |
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# **Voorbereiding: Jupyter Notebook initialiseren**
i... | pypv/notebooks/03_energieanalyse.ipynb |
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# + id="A2mlp-BLpqPf" colab_type="code" colab={"base_u... | ChatBotResponse.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | timeseries.ipynb |
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# PyGSLIB
# ========
#
# Probplot
# ---------------
#
... | pygslib/Ipython_templates/deprecated/probplt_raw.ipynb |
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# # Binary classification single feature
#
# Classific... | classification/ClassificationContinuousSingleFeature.ipynb |
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# hide
# %load_ext autoreload
# %autoreload 2
# ! rm -... | nbs/09_voila_example.ipynb |
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# + id="LHfPLGkqe-Jx" outputId="6d32f44e-3814-4b1d-a9dd-fde87461525e" colab={... | notebooks/train.ipynb |
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# + [markdown] tags=["pdf-title"]
# # Multiclass Suppo... | assignment1/svm.ipynb |
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import netCDF4 as nc
import datetime as dt
import su... | notebooks/plotExamples/SaanichInletDepthSpecificDiet.ipynb |
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# <h1> Experimenting with different models </h1>
#
# I... | quests/data-science-on-gcp-edition1_tf2/07_sparkml_and_bqml/experimentation.ipynb |
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# + [markdown] id="qXwioNNgLMY3" colab_type="text"
# #... | Session9/Day4/Matched_filter_tutorial_mywork.ipynb |
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# <img src="https://github.com/OpenMined/design-assets... | examples/homomorphic-encryption/Tutorial_1_TenSEAL_Syft_Data_Owner.ipynb |
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import cv2
import numpy as np
import sklearn
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# # 제어문
# ## 주요 내용
# 프로그램 실행의 흐름을 제어하는 여러 종류의 제어문(제... | notebooks/python03.ipynb |
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# One of the things you learned about in this chapter ... | Python Data Science Toolbox -Part 2/Using iterators in PythonLand/03.Iterating over iterables (2).ipynb |
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# # RHT example workflow
# ### by... | .ipynb_checkpoints/RHT_example_workflow-checkpoint.ipynb |
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# # Matemática Para Machine Learning
# ## Gradiente D... | Gradiente_Descendente.ipynb |
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# # 02-1데이터 집합 불러오기
# ## 데이터 분석의 시작은 데이터 불러오기부터
# 데이터 ... | chapter_02-1.ipynb |
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import pandas as pd
import json
from datasets impo... | basicEDA.ipynb |
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impo... | examples/doa_inlab.ipynb |
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# # Как писать быстрый код на Python
# ## <NAME>
# Я... | practice/FastPython.ipynb |
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# # Online Trading Customer Attrition Risk Prediction... | examples/TradingCustomerChurnClassifierSparkML.jupyter-py36.ipynb |
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# + id="HKZ5o-QRJxlk" executionInfo={"status": "ok", "timestamp": 16073214172... | neuralNet.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | recommendars.ipynb |
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# # Ungraded lab 1: Linear algebra in Python with nump... | Natural Language Processing with Classification and Vector Spaces/Week 3/NLP_C1_W3_lecture_nb_01.ipynb |
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import os
import pandas as pd
if os.path.exists(h... | codeParse.ipynb |
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# + raw_mimetype="text/restructuredtext" active=""
# .... | source/algorithms/soo/sres.ipynb |
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# <NAME>
#
# -----------------------------... | mowl/examples/Application_of_ontology_embedding.ipynb |
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# + jupyter={"outputs_hidden": false}
# %matplotlib in... | plotting_helper.ipynb |
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# # Our First CNN in Keras
# ### Creating a model bas... | 8. Making a CNN in Keras/8.3 to 8.10 - Building a CNN for handwritten digits - MNIST.ipynb |
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# ## 중첩조건문
# - nested conditional
# - if 블... | lectures/wk3_lec1.ipynb |
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# + [markdown] id="view-in-github" colab_type=... | dNRG.ipynb |
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# # !wget https://malaya-dataset.s3-ap-southeast-1... | pretrained-model/xlnet/tokenizer/preprocessing-pdf.ipynb |
# -*- coding: utf-8 -*-
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# # Superdense Coding Kata
#
# **Sup... | SuperdenseCoding/SuperdenseCoding.ipynb |
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# # Dressmaker - Medium
# Prerequesites
from pyhive i... | Hive/17-2 Dressmaker - Medium.ipynb |
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# # Задание 1.2 - Линейный классификатор (Linear class... | assignments/assignment1/Linear classifier.ipynb |
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import numpy as np
import pandas as pd
import date... | dacon_covid-19/ML/COVID_ML_03_XGBoost.ipynb |
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import numpy as np
from sklearn.metrics import roc_cur... | site/public/courses/DS-2.4/Notebooks/Advanced_Keras/Triplet NN Test on MNIST.ipynb |
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print("Hello,... | src/test.ipynb |
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# # DL Deep Dive - Training
# In this section, we will... | DL_Deep_Dive-Training-keras_mnist_MLP.ipynb |
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# ## SCOTUS justices voting pattern
#
# Here I compare... | SCOTUS/notebooks/SCOTUS-voting-correlation.ipynb |
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# # Logistic Regression with a Neural Network mindset
... | 2. Coursera - Neural Networks and Deep Learning/Week 2/Logistic Regression as a Neural Network/2. Logistic+Regression+with+a+Neural+Network+mindset+v5.ipynb |
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# + id="KWEGFZRvFniW" colab_type="code" colab={"base_uri": "https://localhost... | day5.ipynb |
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#cell-width control
from IPython.core.display import displ... | experiments/ow-on-pseudorandom/6/.ipynb_checkpoints/ow_template-checkpoint.ipynb |
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# # Ex2 - Filtering and Sorting Data
# This time we a... | pandas/02_Filtering_&_Sorting/Euro12/Exercises_with_Solutions.ipynb |
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import os, sys
sys.path.insert(1,... | examples/conv_example.ipynb |
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# First, we wanted a map of ICD (International Classif... | .ipynb_checkpoints/ICD_Diagnostic_and_Procedure_dictionary columns-checkpoint.ipynb |
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# ## Quiz #0204 (Solution)
import pandas as pd
import... | SIC_AI_Quizzes/SIC_AI_Chapter_03_Quiz/sol_0204.ipynb |
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# <!-- dom:TITLE: Day 3: Homework 2 -->
# # Day 3: Hom... | doc/ProjectsExercises/2020/hw2/ipynb/.ipynb_checkpoints/hw2-checkpoint.ipynb |
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# + hide_input=true inputHidden=true language="html"
#... | mirimages-master/oldjupyter/xxx_hiearchdensenet.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # L... | limits.ipynb |
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# # Introdução à Ciência de Dados - UFPB
# Professor: ... | 03.Dist_2_pontos_NumPy.ipynb |
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# # Match Zeta Identities
# The goal of this notebook ... | match_data.ipynb |
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# Lambda School Data Science
#
# *... | module2-convolutional-neural-networks/LS_DS_432_Convolutional_Neural_Networks_Lecture.ipynb |
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# %matplotlib inline
#
#
# The :term:`Events <events>... | stable/_downloads/a663da19dfef335563cab63585276d60/plot_object_annotations.ipynb |
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# # Wide and Deep on TensorFlow (notebook style)
# Co... | workshop_sections/wide_n_deep/wide_n_deep_flow.ipynb |
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import random
import sys
from termcolo... | Wordle_clone.ipynb |
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# # Vanilla RNNs, GRUs and the `scan` function
# In t... | Natural Language Processing/Course 3 - Natural Language Processing with Sequence Models/Labs/Week 2/Vanilla RNNs, GRUs and the scan function.ipynb |
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# # Celeribity Recognition using Amazon Rek... | 02_usecases/archive/05_Celebrity_Detection.ipynb |
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# + active=""
# .. _registrikood_userguide:
#
# Regist... | docs/source/user_guide/clean/clean_ee_registrikood.ipynb |