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# # Credit Fraud Detection: Prediction/Analysis
# --... | projects/Credit Fraud Detection: Prediction/credit_fraud_detection.ipynb.ipynb |
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# ## Leaf Label
# In the example below, leaf labels a... | src/notebooks/401-customised-dendrogram.ipynb |
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# # 通过微调进行迁移学习
# pytorch 一直为我们内置了前面我们讲过的那些著名网络的预训练模型，不... | 05.卷积神经网络（进阶）/22.fine-tune-code/fine-tune.ipynb |
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# + id="IYXT7vhYVZGH" executionInfo={"status": "ok", "timestamp": 16477116753... | first_principle.ipynb |
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# Post Details-
# Link: https://machinelear... | XGBoost-Introduction-Guide/intro-to-xgboost.ipynb |
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# + [markdown] button=false deletable=true new_sheet=f... | .ipynb_checkpoints/tmep-checkpoint.ipynb |
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#ignore
from IPython.core.display import HTML,Imag... | content-queue/05_Model_Scoring.ipynb |
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# # K-Means Demo
#
# KMeans is a basic but powerful cl... | notebooks/kmeans_demo.ipynb |
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# + [markdown] id="ODV-kLWnFCLp"
# ## 1. Basic Design ... | Cat Classification.ipynb |
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import torch
import torchvision.transforms as transfor... | ResNet50.ipynb |
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# # Python session - 3.1
#
# ## Functions and modules
... | Day2/3_1-functions-and-modules.ipynb |
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# ## Deep Q-Network (DQN)
# ---
#
# #### Import the Ne... | 05_deep_q_learning/dqn_her/notebook/.ipynb_checkpoints/dqn_her-checkpoint.ipynb |
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# # Using mulit-linear regressions to pred... | Real Estate Price Forecast/Real Estate Forecast - National Model.ipynb |
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# '
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import os
import pandas as pd
import numpy a... | notebooks/CSE499B/sakib/lightgbm-with-no-scalar.ipynb |
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# # ai-architecture-template - 00_AMLConfiguration.ipy... | notebooks/00_AMLConfiguration.ipynb |
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# # Visualization with Matplotlib
# ## Ge... | day2/08. matplotlib - introduction.ipynb |
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import pandas as pd
import numpy as np
import matplotl... | Lesson06/Activity14/Activity14.ipynb |
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# # 値動きのみでFXに勝てるかDeepLeaningに推測させる
#
# ## 概要
#
# DeepL... | predict_fx_trade.ipynb |
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# + [markdown] colab_type="text" id="MNPgoaG57Zl6"
# # I... | tutorials/demo/student/Interactive_Widget.ipynb |
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# # Children's Height
#
# The purpose of this noteboo... | Linear/Simple/Heights.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | docs/tnpp_diaparse.ipynb |
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# + [markdown] id="gMBVb4ZB2txG" colab_type="text"
# [Open with Colab](https:... | bert_example_based_finetuning.ipynb |
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# + [markdown] colab_type="text" id="t09eeeR5prIJ"
# ##### Copyright 2019 The... | site/en/tutorials/text/text_generation.ipynb |
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import tensorflow as tf
import GRN
import random a... | src/Untitled.ipynb |
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# # Using Null
#
# - teacher
#
# id | dept | name | ph... | Spark/08 Using Null.ipynb |
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import os, sys
'SUMO_HOME' in os.environ
tools = os.... | Sumo Stuff/Nearly RL.ipynb |
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# + [markdown] id="979DKMRxRlER" colab_type="text"
# #... | ODSC_Hackathon.ipynb |
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# # High order Prince methods & Riccati equation
#
# [... | docs/Prince.ipynb |
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# **Hidden Markov models for cracking codes**
#
# In t... | week05_em/hmm-seminar.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://... | part4_variantgenotyping/analysis/part4_variantgenotyping_colab.ipynb |
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# # Index files
# Currently, there are some pr... | examples/index_files.ipynb |
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#Load libraries
import warnings
warnings.filterwarning... | notebooks/Dataset D - Contraceptive Method Choice/Synthetic data generation/GM Dataset D - Contraceptive Method Choice.ipynb |
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# # Import Libraries
# !pip instal... | translations/van-gogh-landscape/train.ipynb |
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# # Example: The Newt... | 1. Starting out.ipynb |
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# ### 딥-러닝 과정 Mulit Layer ... | Deep_Learning/03.MLP_Diabetes_Classification.ipynb |
# -*- coding: utf-8 -*-
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# + id="Zri-DbnCrMJp"
install.packages("tseries")
install.package... | files/seriestemporais_petroleo.ipynb |
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import pandas as pd
import numpy as np
import json... | VacationPy/VacationPy.ipynb |
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# hash: 42121322e9afdadd065c41f4f28fbda90dfc8500... | jupyter_notebooks/regression.ipynb |
# coding=utf-8
# Copyright 2021 The Google Research 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 applicab... | recommender/runner.ipynb |
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import torch
from functools import partial
from t... | quantized_mobilenetv4.ipynb |
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# # Test tensorflow gpu #
# +
import tens... | Training/CRNN-2LSTM-DatasetScaling.ipynb |
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# # Градиентный бустинг "в лоб"¶
# ### 1. Считайте та... | 7_week_1_independent_work_gradient_boosting.ipynb |
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# + [markdown] customInput originalKey="4dbd5617-33f8-4544-82d3-0f96e82c50e6" showInput=false
# ## Tutorial: **Hidden Markov model**
# + [mar... | tutorials/Hidden_Markov_model.ipynb |
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# # Skydipper datasets for Deep Learning
#
# In this n... | notebooks/Skydipper_datasets.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Project_6_Notebook_cfc.ipynb |
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# # NSW naturalizations data from NSW State Archives
... | nsw_naturalisations.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}... | chapter_03_to_06/abstract_datatypes.ipynb |
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# + [markdown] slideshow={"slide_type": "-"}
# <br>
# ... | 06_EPO/e-TeenAstronomyCafe/01_Lives_and_Deaths_of_Stars/Lives_and_Deaths_of_Stars.ipynb |
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# # Problem Description
#
# We want to find out how... | 4-poisson-inverse-conductivity-posterior-consistency/poisson-inverse-conductivity-posterior-consistency.ipynb |
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import pyclesperanto_prototype as cle
impo... | demo/neighbors/quantitative_neighbor_maps.ipynb |
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# # Earth's geomagnetic polarity timescale and the Gam... | week_06/assignment/.ipynb_checkpoints/W6_Assignment_Geomag-checkpoint.ipynb |
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# Adaptive Distances
# ==================
# In this e... | doc/examples/adaptive_distances.ipynb |
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# default_exp optimiz... | nbs/12_optimizer.ipynb |
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# ## Deploy <font color='red'>For Seller t... | aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/ModelPackage/Sample_Notebook_Template/title_of_your_product-Model.ipynb |
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# # Demo: fetching positions of S-MODE in-situ assets
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# # Visualising transcriptomes with IGV... | RNA-Seq/transcriptome-visualisation.ipynb |
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# # Aula 13 - Reinforcement learning
#
# ### Temas:
# ... | lessons/13 - Reinforcement learning.ipynb |
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# + application/vnd.databricks.v1+cell={"inputWidgets"... | notebooks/byes.ipynb |
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# + [markdown] id="0sVgU84dbDxJ"
# # Midterm - Correct... | site/_build/jupyter_execute/assignments/midterm/hm.ipynb |
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# + [markdown] id="view-in-github"
# <a href="https://colab.research.google.c... | Publish_SQL_based_endpoints_on_NGINX_log_analysis.ipynb |
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# # Keras MNIST Model Deployment
#
# * Wrap a Tensorf... | examples/models/keras_mnist/keras_mnist.ipynb |
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# # Machine learning using scikit-learn
#
# There are ... | tutorial/05_MachineLearning.ipynb |
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# # Classifying 1984 US House of Representa... | examples/jhboyle/1984_Congressional_Voting_Classification.ipynb |
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# + id="R-iRSUmj4MJ4"
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im... | AmazonReview.ipynb |
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# <h1><Center>Household power consumption forecast usi... | LSTM multi-step time series forecasting of household power consumption..ipynb |
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"""
Estimating the causal effect of so... | docs/_build/.jupyter_cache/executed/384bbed82e7d63ab2e9be1c4d93b6a79/base.ipynb |
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# <a href="https://apssdc.in"><img src="https://camo.g... | Notebooks/Day16_Comprehensions_and_Special_Functions_in_Python.ipynb |
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;; + vscode={"languageId"... | ch1/1.2/ex.1.27.ipynb |
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# # Dynamic cross-correlation analysis
import py... | code/Notebooks/pytraj_xcorr.ipynb |
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... | Cap01_Introduccion.ipynb |
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# # Dream Bank
#
# # Part 1: Text Preprocessing
#
# **... | notebooks/Dream_Bank_Data_Preprocessing.ipynb |
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# ## L’essentiel sur les arbres... | S2/ML/TME/TME1/TME1.ipynb |
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# # Secure sorting networks explained
#
# In this note... | demos/SecureSortingNetsExplained.ipynb |
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# **Корректность проверена на Python 3.6:**
# + pandas... | course2/week3/Preprocessing_LR_Coursera.ipynb |
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# !python main.py gen --model-path='checkpoints/tang... | _book/img_input/.ipynb_checkpoints/Debug-checkpoint.ipynb |
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# # Object Mutability
#
# Object is made up:
#
# - Typ... | python-deepdive/deepdive1/section03/section_03_20.ipynb |
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# # Batch processing with Argo Worfklows and HDFS
#
# ... | examples/batch/hdfs-argo-workflows/hdfs-batch.ipynb |
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# # Polynomial Interpolation
# +
import numpy as np
i... | numerical_analysis/report2_codes.ipynb |
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# # Querying the Topology to Find Neighbors
import op... | examples/tutorials/network/finding_neighbor_pores_and_throats.ipynb |
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# +
import h5py
from Bio import SeqIO, AlignIO
import ... | notebooks/Pfam2HDF5.ipynb |
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# # Plot Throughput of Experiment 2.2 version 3
impor... | PlanB/CPU_utilization_Experiment/version3_Experiment_style/Experiment2_2/Edge4_iperf/Plot_Throughput_experiment_2_2_v3.ipynb |
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# # Domain wall relaxation in a nanowire
# This is a ... | doc/ipython_notebooks_src/tutorial-domain_wall_relaxation_example.ipynb |
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# ### GridSearch & Pipelines
# GridSearch is an optimi... | 4-Machine_Learning/1-Supervisado/9-GridSearchCV & Pipelines/grid_search - Clase.ipynb |
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fr... | antigenic_evolution/.ipynb_checkpoints/process_h3n2_data-checkpoint.ipynb |
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# + [markdown] id="_lmvKIjL6gyq"
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# + colab={"base_uri": "https://localhost:8080/"} id="21QsC7Kfuc-U" outputId=... | Audio_Recognition.ipynb |
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import sys
from typing import Dict, List, Any, Tu... | tutorial/examples/download_recent_posts.ipynb |
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# %load_ext autoreload
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# ## Entrada y Salida de Datos en formatos Heterogeneo... | topologias/Lectura de diferentes formatos de datos con Pandas.ipynb |
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import tensorflow as tf
gpu_fraction = 0.1
gpu_opt... | AttensionModel-random-wrting-generate.ipynb |
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# !pip install torch==1.8.2+cu111 torchvis... | drowsinessYOLOv5.ipynb |
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# ## Intro to information extraction from text
#
# Mos... | notes/text.ipynb |
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# # Expand_grid : Create a dataframe from all combinations of inputs.
# ## B... | examples/notebooks/expand_grid.ipynb |
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# + [markdown] deletable=true editable=true
# ## GA Da... | .ipynb_checkpoints/GA Data Science Final Project - 3- NLP-checkpoint.ipynb |