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# [![image](https://colab.research.google.com/assets/c... | examples/notebooks/52_netcdf.ipynb |
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# + [markdown] id="9lAsyeOwFnoX"
# # CSCE 623 Homework... | hw3.ipynb |
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# Detector Face with CV2
# +
import os,cv2,keras
impo... | Train/CV2.ipynb |
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# # MPIJob and Horovod Runtime
#
# ## Running distribu... | docs/runtimes/horovod.ipynb |
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import numpy as np
import torch
torch.set_printoptions... | lectures/white_whine_data.ipynb |
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# ## The QLBS model for a European option
#
# Welcome ... | m3-ex2/dp_qlbs_oneset_m3_ex2_v3.ipynb |
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# + tags=["parameters"]
cfg_times = 3
cfg_lr = 0.02/4
... | references/mmdetection/dev/tmpl_s1_step.ipynb |
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# + id="ZlnGn4MT_1jC" outputId="1454afb8-4ca3-4951-c8c3-9fd52ee507f3" colab={... | 12_Deceptive_Opinion_Detection_using_BERT_without_Fine_Tune.ipynb |
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# + run_control={"frozen": false, "read_only": false}
... | notebooks/tutorial/DFAUnit2.ipynb |
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kos = '../out/rev_sequencing_kos.tsv'
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# %matplotl... | notebooks/sequencing_kos.ipynb |
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# # Naming of Gluon Parameter and Blocks
#
# In gluon, each Parameter or Block has a name (and prefix). Parameter names are specified by users... | static_websites/python/docs/_sources/tutorials/packages/gluon/naming.ipynb |
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import numpy as np
import pandas as pd
import matplotl... | ipynb/UCI-data-set---Multivariate-data---classification.ipynb |
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import numpy as np
import glob, os
import re
import PI... | machineLearning/deepLearning/.ipynb_checkpoints/CNN-checkpoint.ipynb |
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# **Math - Linear Algebra**
#
# *Linear Algebra is the... | math_linear_algebra.ipynb |
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import aiohttp
import asyncio
import time
from IP... | explore-aqmd-urls.ipynb |
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# # Tutorial Goal
# This tutorial aims to show how RT... | ipynb/tutorial/07_PerfAnalysis.ipynb |
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# + id="WWxwZ9wtnTZE" colab_type="code" colab={"base_uri": "https://localhost... | Part2/moment_train/hsi.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | TEST_Zero_Shot_Pipeline.ipynb |
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# # TensorFlow & Keras - Basics of Deep Learning
# ##... | Day03/deep_learning.ipynb |
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# layout: post
# title: "Basics of panda"
# cat... | _drafts/2021-02-01-Basic-of-pandas.ipynb |
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# # Matplotlib: Beyond the basics
#
# ## Status and pl... | lectures/10-matplotlib_beyond_basics/10-matplotlib_beyond_basics.ipynb |
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# # Retail Demo Store - Personalization Wor... | workshop/1-Personalization/1.1-Personalize.ipynb |
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# ## ノイズ耐性1
from ml.nn import *
from datasets.dataset... | robot_intelligence_noise1.ipynb |
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# ! wget -N http://archive.ics.uci.edu/ml/machine-lear... | ml/lab1.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as p... | tools/.ipynb_checkpoints/draw_bbox_recall-checkpoint.ipynb |
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# Lemmatizing
from nltk.stem import WordNetLemmatizer... | lemmatizing.ipynb |
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# # Huggingface Sagemaker-sdk - Getting Started Demo
#... | sagemaker/01_getting_started_pytorch/sagemaker-notebook.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | titanic.ipynb |
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# # 02- Array & Linked List
# ## Table of Contents:
#... | 03. Data Structure and Algorithm/02- Array & Linked List.ipynb |
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import mindspore
import mindspore.nn as nn
from mindsp... | 2-1.TextCNN/TextCNN.ipynb |
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# <script async src="https://www.googletagmanager.com/... | Tutorial-Psi4_tetrads.ipynb |
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# # Introduction
# ### Download the raw da... | notebooks/blog_materials/Time_Series_Forecasting_with_Unstructured_Data_and_Amazon_SageMaker_Neural_Topic_Model/1_preprocess.ipynb |
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from sklearn import datasets
... | SVM.ipynb |
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# # 文本处理与增强
#
# [![](https://gitee.com/mindspore/docs/... | docs/mindspore/programming_guide/source_zh_cn/tokenizer.ipynb |
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# # Aplicando Python para análisis de precios: descarg... | Módulo 2/Clase12_ManejoAnalisisDatosPandas.ipynb |
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# Download this page as a jupyter notebook at [Lesson ... | 1-Lessons/Lesson03/dev_src/.ipynb_checkpoints/ENGR-1330-Lesson03old-checkpoint.ipynb |
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from numpy import log10, asarray, polyfit, ceil, a... | Python/COVID-19 Plots.ipynb |
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# + [markdown] colab_type="text" id="1BtkMGSYQOTQ"
# # Train a gesture recogn... | tensorflow/lite/micro/examples/magic_wand/train/train_magic_wand_model.ipynb |
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# # Segment
#
# Description
# +
# %l... | notebook/segment/2.0-segment.ipynb |
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# # Profiling PyTorch Multi GPU Single Node Training J... | sagemaker-debugger/pytorch_profiling/pt-resnet-profiling-multi-gpu-single-node.ipynb |
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# ### Dummy data for classification
# +
import seabor... | content/sklearn/.ipynb_checkpoints/Metrics - Classification Report Breakdown (Precision, Recall, F1)-checkpoint.ipynb |
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# <table>
# <tr><td align="right" style="backgroun... | bronze/B20_Quantum_Coin_Flipping.ipynb |
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# %matplotlib inline
#
# # Comparison of LDA and PCA ... | scikit-learn-official-examples/decomposition/plot_pca_vs_lda.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | DataScience/DS-Unit-1-Sprint-2-Statistics/module1/LS_DS_121_Statistics_Probability_Assignment.ipynb |
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# # Step 5.3 Parameter Tuning with C
# In this noteboo... | Step_5.3_Parameter_Tuning_C.ipynb |
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# ## Python Cleaning Up Text Files
import os
fname =... | Python Cleaning Up Text Files.ipynb |
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from gs_quant.common import PayReceive, Currency
from ... | gs_quant/documentation/02_pricing_and_risk/00_instruments_and_measures/examples/01_rates/000107_calc_swap_risk_historically.ipynb |
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# ## Perform Analysis on Athletes
#
# This file reads ... | 2-Luther_Project/code/.ipynb_checkpoints/Luther_Regression-checkpoint.ipynb |
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# # Importazione dati
# Questo notebook verrà usato pe... | SocialPulse(noCC)/.ipynb_checkpoints/Import+Merge_Final-checkpoint.ipynb |
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# + [markdown] id="aFifDWoz20QY"
# # 0. Setup
#
# + id="IWemigXMuUqk"
import... | CS470_PJ.ipynb |
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import pandas as pd
url1 = 'https://www.cbsspo... | content/lessons/12/End-To-End-Example/CBS Sports.ipynb |
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import numpy as np
import pandas as pd
... | notebooks/dpdg.ipynb |
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# # OpTaliX: Lens data items surface
# T... | _build/html/_sources/OpTaliX_LDI_surface.ipynb |
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"""
Simple TensorFlow exercises
Y... | Assignment1/assignment1.ipynb |
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# ## Please input your directory for th... | src/gluonts/nursery/QRX-Wrapped-M5-Accuracy-Solution/3. code/3. predict/2-3. nonrecursive_store_dept_PREDICT.ipynb |
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from molmap import model as molmodel
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# ## Exercise 5.01: Predicting sales from advertising ... | Chapter05/Exercise5.01-5.04.ipynb |
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# # Demonstration of Mlflow via energy forecasting.
#
... | mlflow/01-MLflow.ipynb |
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# + [markdown] id="2tr1DfOiz9cb" colab_type="text"
# #... | 20_newsgroups_automl.ipynb |
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# + pycharm={"name": "#%%\n"}
# -*- coding: utf-8 -*-
"""
Created ... | Optimization_new2_electricity_households.ipynb |
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# %matplotlib inline
from sklearn import svm
impor... | libsvm-learning/SVR.ipynb |
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import pandas as pd
import numpy as np
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for i in range(2):
for j in range(3):
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import cfbd
import datetime
import numpy as np
import ... | Talking Tech/EloRatings.ipynb |
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# # Tweets Analysis
# ## 1. Import Librari... | tweets-analysis.ipynb |
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# Python packages
from itertools import chain
imp... | analysis/.ipynb_checkpoints/Analysis-Copy1-checkpoint.ipynb |
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import pandas as pd
import numpy as np
import fo... | covid _19 analysis.ipynb |
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# + [markdown] id="vi... | notebooks/03_example_script_for_colab_final_version.ipynb |
# # [FMA: A Dataset For Music Analysis](https://github.com/mdeff/fma)
#
# <NAME>, <NAME>, <NAME>, <NAME>, EPFL LTS2.
#
# ## Free Music Archive web API
#
# All the data in the `raw_*.csv` tables was collected from the Free Music Archive [public API](https://freemusicarchive.org/api). With this notebook, you can:
# * rec... | webapi.ipynb |
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import json
import requests
# %matplotlib inline
impor... | notebooks/.ipynb_checkpoints/Test PANGAEA Datasets - Results (Before,After)-checkpoint.ipynb |
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# # Numba parallel
import numpy as np
from numba impo... | templates/02_numba_parallel/02_numba_parallel.ipynb |
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# + [markdown] id="AYV_dMVDxyc2"
# [
# language: python
# name: python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east... | 2-lineage-train-assess-bias-tune-registry-e2e.ipynb |
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import numpy as np
import pandas as pd
from os imp... | WorldCloud.ipynb |
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# + [markdown] origin_pos=0
# # 异步计算
# :label:`sec_async`
#
# 今天的计算机是高度并行的系统，由多个CPU核、多个GPU、多个处理单元组成。通常每个CPU核有多个线程，每个设备通常有多个GPU，每个GPU有多个处理单元。总之... | submodules/resource/d2l-zh/pytorch/chapter_computational-performance/async-computation.ipynb |
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# # Tutorial 6 (:-})
# ## Constructing Basic Shapes ... | Constructing basic shapes in opencv/Constructing Basic Shapes in OpenCV.ipynb |
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# # 6.4 컨브넷을 사용한 시퀀스 처리
# 이 노트북은 [케라스 창시자에게 배우는 딥러닝](... | _books/DeepLearningFromKeras/Part2/Chapter6/6.4.ipynb |
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# + active=""
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# ### 27-Jan-2020
# 1. Load Train and Test datasets i... | 4.a Preparation on the entire dataset.ipynb |
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# + [markdown] colab_type="text" id="qN8P0AnTnAhh"
# ##### Copyright 2020 The... | docs/openmined2020/openmined_conference_2020.ipynb |
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# # Setup
# +
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# # import modules
import requests
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# + id="QUVT0_NQGkyF" colab_type="code" colab={}
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#
# # Changing colors of lines i... | matplotlib/gallery_jupyter/misc/bbox_intersect.ipynb |
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# # Chapter 2 - Random Graph Models
#
# In the first part... | Python_Notebooks/Chapter_2.ipynb |
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#before running the notebook, download yelp datase... | yelp_reviewset_mxnet.ipynb |
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# # Data Bootcamp: Code Practice A (... | Code/notebooks/bootcamp_practice_a_answerkey.ipynb |
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# # Classification de documents... | S2/RITAL/TAL/TME/TME1/.ipynb_checkpoints/BenchmarkClassif-checkpoint.ipynb |
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# # 10 Dimension reduction
#
# Part of ["Introduction ... | 10_Dimension_reduction.ipynb |