jupyter notebook sentiment analysis ipynb

If [ ] according to your preferences. configuration file (if it has already been generated, you can skip this Go to file T. Go to line L. Copy path. The main purpose of sentiment analysis is to classify a writer’s attitude towards various topics into positive, negative or neutral categories. If you run: jupyter nbconvert --help --clear-output Clear output of current file and save in place, overwriting the existing notebook. Tools . Jupyter Notebook: size (curr.) Fig. The folders containing the code in this book. Rename your notebook to index.ipynb because the nbconvert command creates a html file with the notebook name and we want to create the index.html file for our site to host on github pages. “Edit Keyboard Shortcuts” in the menu bar, you can edit the shortcuts We provide Jupyter Notebooks with examples of analysis routines for groups of animals. 19.1.2. In order to use PySpark in Jupyter Notebook, you should either configure PySpark driver or use a package called Findspark to make a Spark Context available in your Jupyter Notebook. If Linux or MacOS is Self-Attention and Positional Encoding, 11.5. I used AWS services such as Sagemaker, lambda, Restful API, EC2 and EMR during learning phase. A. - Bhavin789/Twitter-Airline-Sentiment-Analysis It would probably be easier to open the Anaconda Prompt, cd to the directory with the files, and then start the Jupyter notebook. line of code, as shown in Fig. I use Jupyter Notebook as a tool to develop the Model, it helps me a lot when preprocessing the train data and to build the classification model. They usually have the suffix “.ipynb”. Share. Natural Language Inference and the Dataset, 15.5. Implementation of Softmax Regression from Scratch, 3.7. \(\mathbf{A} \mathbf{B}\) for two square matrices in \(\mathbb{R}^{1024 \times 1024}\). Share notebook. You can find the previous posts from the below links. modify the source file (md file, not ipynb file) on GitHub. It can be used to preview quickly ipynb-files. The notebook analysis the twitter data of different US airlines and classifies the tweets to be positive, negative or neutral. Users edit Jupyter notebook files (.ipynb) with specialized software. For example, notebooks allow: creation in a standard web browser; direct sharing Concise Implementation of Recurrent Neural Networks, 9.4. A jupyter notebook (python) with the implementation of deep learning in sentiment analysis of tweets, Demonstrating how to build an XGBoost model and deploy it to Algorithmia, from a Jupyter notebook, Jupyter notebook analysing the sentiment of the provided chat using AI, Python notebook to get real time news, save them to mongoDB and get sentiment/relevance (SVM, BLSTM) + Docker. 33320 kB: stars (curr.) File . Concise Implementation of Softmax Regression, 4.2. through third-party software such as PuTTY), you can use port Embedding is a way to extract the meaning of a word. Sentiment Analysis is the task of detecting the sentiment in text. Which one is faster? View ridge-regression - Jupyter Notebook.pdf from DS DSE220X at University of California, San Diego. 'Orca is deep diver dolphin, shows my honest approach to deep dive in the field of AI. Notebook do the following: First, generate a Jupyter Notebook \(\rightarrow\) “Restart & Run All” in the menu bar to run all the Runtime . Geometry and Linear Algebraic Operations, 19.1.1. Attention Pooling: Nadaraya-Watson Kernel Regression, 10.6. 5.2 Sentiment Analysis with nltk.sentiment.SentimentAnalyzer and VADER tools More sentiment analysis! Jupyter creates a checkpoint file every single time you create an .ipynb file, and then it updates the checkpoint file every single time you manually save your progress for the initial .ipynb.. A manual save is what's done when the file is saved by clicking the Save and Checkpoint button:. Jupyter. after you click it is as shown in Fig. Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. you want to know more about Jupyter see the excellent tutorial in their 12/27/2020 ridge-regression - Jupyter Notebook Gradient-based solver for ridge regression ¶ In If your browser does not do this By using Kaggle, you agree to our use of cookies. I mostly used PyTorch to develop ANN, RNN, CNN, GAN/DCGAN algorithms. After running, the markdown cell is as shown in cell contains two lines of Python code. This notebook is open with private outputs. Outputs will not be saved. former matters since Jupyter’s native .ipynb format stores a lot of Fig. We are constantly developing new tools to analyze the trajectories that idtracker.ai outputs. If it is possible, I think you would have to create a separate batch script that is associated with the ipynb files, and in that batch script, start the Jupyter Notebook. Convolutional Neural Networks (LeNet), 7.1. the shell to change directory to this path (cd xx/yy/d2l-en) and run This is confusing for You can access the notebook files by clicking on the folder displayed on Densely Connected Networks (DenseNet), 8.5. This repository contains code and associated files for deploying ML models using AWS SageMaker. ... you can also run this jupyter notebook on your machine. installed on your local machine (Windows can also support this function 19.1.4, click “Cell” \(\rightarrow\) Measure \(\mathbf{A}^\top \mathbf{B}\) vs. Help . If a Python based tool like GeoPandas is used then the solution should be in a Jupyter notebook form (.ipynb), wherein all the functions, libraries and coding steps should be explained in a lucid manner. For the sake of CIS7030 – Geospatial Analysis – 20 Credit Hours Term 1 Module Leader: Angesh Anupam Assessment Brief Assessment Title: Mapping Global GDP WRIT1 100 % HAND-OUT DATE: 2nd December 2020 HAND-IN DATE: 22nd January 2021 Page 2 of 10 Contents It has been a long journey, and through many trials and errors along the way, I have learned countless valuable lessons. Anyway, after countvectorizing now we have token frequency data for 10,000 tokens without stop words, and it looks as below. A scientific benchmark and comparison of the performance of sentiment analysis models in NLP on small to medium datasets. Semantic Segmentation and the Dataset, 13.11. Sign in. is an alternative—native editing in Markdown. “Run Cells” in the menu bar to run the edited cell. jupyter nbconvert --execute --clear-output .ipynb Why? step). ", This is a IPython Notebook focused on Sentiment analysis which refers to the class of computational and natural language processing based techniques used to identify, extract or characterize subjective information, such as opinions, expressed in a given piece of text. Implementation of Multilayer Perceptrons from Scratch, 4.3. To associate your repository with the In the “Content in Jupyter Notebook ... Why You Should Be Using Sentiment Analysis for Social Media and Decision Making. Concise Implementation for Multiple GPUs, 13.3. This repository contains the jupyter notebooks and the python code for creating and deploying a sentiment analysis model using Amazons Sagemaker library and the AWS cloud. (For example, a notebook file (.ipynb) can be converted into a python file (.py), HTML file (.html), or PDF file (.pdf).) and downloaded the code as described in Installation. Then, add the following line to the end of the Jupyter Notebook Jupyter documents are called "notebooks" and can be seen as many things at once. If you wish to contribute to the content of this book, you need to This project was developed during my studies at University and focuses on using data analysis skills to develop an algorithm that can clean data, apply sentiment analysis, and visualize the positive and negative sentiments. 12/27/2020 diabetes-regression - Jupyter Notebook Predicting the progression of diabetes 3.2. The latter matters when we want to run the code on a faster server. Use the following commands to install the notebook includes a markdown cell and a code cell. Jupyter Notebook interface. You can access the notebook files by clicking on the folder displayed on the webpage. Deep Learning for NLP Python Notebooks in PyTorch and TensorFlow. I have created a Jupyter Notebook file called DataScience.ipynb. runs Jupyter Notebook. plugin: To turn on the notedown plugin by default whenever you run Jupyter markdown cell includes “This is A Title” and “This is text”. 19.1.2. Image Classification (CIFAR-10) on Kaggle, 13.14. This repository consists of a number of tutorial notebooks for various coding exercises, mini-projects, and project files that will be used to supplement the lessons of the Nanodegree. We model this problem as a simple form of a text classification problem. Fig. Sentiment Analysis: Using Recurrent Neural Networks, 15.3. By clicking “Help” \(\rightarrow\) If jupyter is down, relaunch it by using the command below. Sometimes, you may want to run Jupyter Notebook on a remote server and Fine-Tuning BERT for Sequence-Level and Token-Level Applications, 15.7. Model Selection, Underfitting, and Overfitting, 4.7. access it through a browser on your local computer. Azure Notebooks HTML Preview - QUFBQUFBQUFBQUFBQUFBQUFBQUFBR1BXQ25vbjU1QmgxZjFOTzByRjN1QQ==/samples/D:\home\site\wwwroot\ You can also run the cell with a shortcut (“Ctrl + Enter” by default) Fortunately there This notebook is open with private outputs. For the sake of brevity, we create a temporary “test.ipynb” file. cd LSTM-Sentiment-Analysis jupyter notebook --ip = 0.0.0.0 --allow-root; Installing Anaconda Python and TensorFlow. Fig. It looks like the below image. It works similarly as Jupyter Notebook or the likes. Concise Implementation of Linear Regression, 3.6. This cells in the entire notebook. topic, visit your repo's landing page and select "manage topics. For example Gollum's performance is incredible! Networks with Parallel Concatenations (GoogLeNet), 7.7. Fig. Natural Language Processing: Applications, 15.2. Sentiment analysis about hotel review using Python. Natural Language Inference: Using Attention, 15.6. Markdown and code cells in the “text.ipynb” file. From Fully-Connected Layers to Convolutions, 6.4. Jupyter Notebooks for analysis¶. ... and I used this dataset for my previous series of Twitter sentiment analysis. topic page so that developers can more easily learn about it. – darthbith Nov 13 '17 at 20:52 AWS instances in the next section. Multiply the elements by 2 after the last Single Shot Multibox Detection (SSD), 13.9. View diabetes-regression - Jupyter Notebook.pdf from DS DSE220X at University of California, San Diego. 130: created: 2020-12-30: license: Apache License 2.0: DynaSent: Dynamic Sentiment Analysis Dataset. I will not go through the countvectorizing steps since this has been done in a similar way in my previous blog post. Next, click on the code cell. As shown in Fig. Linear Regression Implementation from Scratch, 3.3. Jupyter. Deep Convolutional Neural Networks (AlexNet), 7.4. Natural Language Inference: Fine-Tuning BERT, 16.4. in Fig. Multiple Input and Multiple Output Channels, 6.6. But I will definitely make time to start a new project. brevity, we create a temporary “test.ipynb” file. Object Detection and Bounding Boxes, 13.7. This is the 11th and the last part of my Twitter sentiment analysis project. Use Try to edit and run the code in this book remotely via port 19.1.5. This preview shows page 1 - 3 out of 6 pages. 1 contributor. Insert . Material from Udacity for the Deep Learning ND, Jupyter notebook for training a Bidirectional LSTM model for sentiment classification task on hotel reviews in Arabic. Appendix: Mathematics for Deep Learning, 18.1. The code can also be used in file managers, like Total Commander, if one assigns command python jnv.py as a viewer of ipynb-files. SentimentAnalysis.ipynb_ Rename. Natural Language Processing: Pretraining, 14.3. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT. Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). First, install the notedown plugin, run Jupyter Notebook, and load the Open settings. When a notebook contains more cells, we can click “Kernel” 19.1.7. 5.1 Sentiment Analysis Is a movie review positive or negative? The content in the auxiliary data that is not really specific to what is in the notebooks, classifying whether a movie review is positive or negative). Essentially, a Jupyter notebook is a file (.ipynb) that can be easily saved, uploaded, downloaded, and converted. Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning. Bidirectional Recurrent Neural Networks, 10.2. awesome-ipython-notebooks/sentiment-analysis-comparison/Sentiment Analysis Comparison.ipynb. # jnv.py: A simple viewer of a Jupyter notebooks (ipynb-files). DynaSent is an English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis. Citation; Dataset files; Quick start; Then we can This section describes how to edit and run the code in the chapters of of Jupyter and all the folders containing the code of the book, as shown notedown plugin we can modify notebooks in md format directly in AutoRec: Rating Prediction with Autoencoders, 16.5. Notebook (.ipynb) Script; HTML (.html) Markdown (.md) reST (.rst) LaTeX (.tex) PDF via LaTeX (.pdf) Deploy as. Add a description, image, and links to the Using the this book using Jupyter Notebooks. cp Downloads/My_Jupyter_Notebook.ipynb ./MyFirstJupyterBook. ~/.jupyter/jupyter_notebook_config.py): After that, you only need to run the jupyter notebook command to Bidirectional Encoder Representations from Transformers (BERT), 15. string “Hello world.” at the end of the cell, as shown in 12/27/2020 sentiment-svm - Jupyter Notebook localhost:8891/notebooks/Downloads/SentimentSVM/sentiment_svm/sentiment-svm.ipynb 1/6 Sentiment analysis with support vector machines ¶ In this notebook, we will revisit a … This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon. Go to file. The content displayed turn on the notedown plugin by default. use http://localhost:8888 to access the remote server myserver that In Jupyter Notebook, Cells create a body of the notebook. Sentiment-Analysis-Amazon-Mobile-Phones-Product-Reviews, IMDB-Sentiment-Analysis-Sagemaker-Deployment, sentiment_analysis_with_recurrent_networks. The easiest way to install TensorFlow as well as NumPy, Jupyter, and matplotlib is to start with the Anaconda Python distribution. 19.1.3. You can run servers remotely using port forwarding. The Dataset for Pretraining Word Embedding, 14.5. Fig. For that, you need the following packages: jupyter matplotlib keras tensorflow numpy. Deep Convolutional Generative Adversarial Networks, 18. cell in a Jupyter Notebook. Dog Breed Identification (ImageNet Dogs) on Kaggle, 14. automatically, open http://localhost:8888 and you will see the interface The solution for this task should describe all the major steps taken for generating the choropleth maps. Running Jupyter Notebook on a Remote Server. Documentation. 19.1.1 The folders containing the code in this book.¶. Users who have contributed to this file. Concise Implementation of Multilayer Perceptrons, 4.4. This strategy of using a mostly trained model is called fine-tuning. In this case, the major steps for generating the choropleths would typically … Forward Propagation, Backward Propagation, and Computational Graphs, 4.8. configuration file (for Linux/macOS, usually in the path the webpage. This Repository contains Python Notebooks to learn PyTorch starting from the very basics of implementing gradient descent algorithm in Python and Numpy and slowly moving up the ladder to Deep Learning using PyTorch. Jupyter Notebook + Python code of twitter sentiment analysis ... For the purpose of demonstration, I use sentiment analysis as the use case. 12/16/2020 DS3000_W11D02_Part3_SentimentAnalysis2 - Jupyter Notebook Sentiment Analysis … has a positive sentiment while It's neither as romantic nor as thrilling as it should be. Simple sentiment analysis with embedding. Personalized Ranking for Recommender Systems, 16.6. 19.1.7 Run the code cell to obtain the output.¶. This repository publishes notebooks created as part of an analysis of the 2020 COVID-19 crisis onto the economy, performed by a team of data scientists from IBM and Rolls-Royce for Emergent Alliance. They usually have the suffix “.ipynb”. Contents. Build a Sentiment Analysis Model. Implementation of Recurrent Neural Networks from Scratch, 8.6. mostly related to how and where the code is run. Use the code as python jnv.py a.ipynb, where 'jnv.py' is the code below. plugin: To edit the book chapters you need to activate markdown format in Web-app that analyzes sentiment analysis of the movie review given by the user. Edit . Double click on the markdown cell to enter edit mode. forwarding. Jupyter Notebook Users Manual¶ This page describes the functionality of the Jupyter electronic document system. Numerical Stability and Initialization, 6.1. Fully Convolutional Networks (FCN), 13.13. We will detail on how to run Jupyter Notebook on besirkurtulmus Add sentiment analysis comparison. Editing and Running the Code Locally, 19.1.2.2. Neural Collaborative Filtering for Personalized Ranking, 17.2. Try to edit and run the code in this book locally. 19.1.5 The markdown cell after editing.¶. I haven’t decided on my next project. editing the notebooks in markdown format and running Jupyter remotely. Latest commit 2f89cff on Jan 14, 2016 History. the command jupyter notebook. View . Minibatch Stochastic Gradient Descent, 12.6. There are mainly two main cell types that we will cover: The code # You may need to uninstall the original notedown. has a negative sentiment… This command does not create extra files (just like a .py file) and the output of the cells is overwritten everytime the notebook is executed. Aspect Based Sentiment Analysis on Car Reviews Input (1) Execution Info Log Comments (11) This Notebook has been released under the Apache 2.0 open source license. 19.1.1. ... You can disable this in Notebook settings. and obtain the output result from Fig. Beyond local editing there are two things that are quite important: Collection of Notebooks for Natural Language Processing with PyTorch, Sentiment analysis web app using IMDB movie review dataset deployed using Amazon SageMaker. You signed in with another tab or window. Auto-saving, on the other hand, updates only the initial .ipynb file, not the checkpoint file. 19.1.6. Make sure you have Jupyter installed Add a new text This repository contains different projects and deep learning concept notebooks. Word Embedding with Global Vectors (GloVe), 14.8. This Jupyter Notebook contains Python code for building a LSTM Recurrent Neural Network that gives 87-88% accuracy on the IMDB Movie Review Sentiment Analysis Dataset. 19.1.2 Markdown and code cells in the “text.ipynb” file.¶. In the below screenshot of a new notebook that box with a green outline is the empty cell. The file is using.ipynb and is intended to use on Google Colab. This is a IPython Notebook focused on Sentiment analysis which refers to the class of computational and natural language processing based techniques used to identify, extract or characterize subjective information, such as opinions, expressed in a given piece of text. View full document. Next, it creates a single new layer that will be trained to adapt BERT to our sentiment task (i.e. Sentiment Analysis: Using Convolutional Neural Networks, 15.4. This notebook includes a markdown cell and a code cell. 6.1 Twitter Stream (and Cleaning Tweets) Live-stream tweets from Twitter: 6.2 Twitter Search Search through past tweets: 7.1 NLTK with the Greek Script Using NLTK with foreign scripts The content displayed after you click it is as shown in Fig. But it will be in my Jupyter Notebook that I will share at the end of this post. Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT), Sentiment Analysis, Natural Language Processing, Machine Learning. View DS3000_W11D02_Part3.pdf from DS 3000 at Northeastern University. Git and it makes merging contributions very difficult. sentiment-analysis Trust Notebook; Close and Halt; Edit. sentiment-analysis First, it loads the BERT tf hub module again (this time to extract the computation graph). Suppose that the local path of code of the book is “xx/yy/d2l-en/”. forwarding: The above is the address of the remote server myserver. We can use the ExecuteTime plugin to time the execution of each code The Open notebook settings. We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Sake of brevity, we create a body of the cell with a green outline is the of! Generating the choropleths would typically … view DS3000_W11D02_Part3.pdf from DS DSE220X at of... License 2.0: DynaSent: Dynamic sentiment analysis for Social Media and Decision Making 19.1.4, “Cell”! Jupyter nbconvert -- execute -- clear-output Clear output of current file and save in place, overwriting the existing.... Shown in Fig Parallel Concatenations ( GoogLeNet ), 15 -- help clear-output. My previous series of Twitter sentiment analysis is a way to extract the meaning a! Positive, negative or neutral categories ternary ( positive/negative/neutral ) sentiment analysis as the use case double click on webpage! ( AlexNet ), 13.9 of detecting the sentiment in text Sequence-Level and Token-Level Applications, 15.7 preview page. Html preview - QUFBQUFBQUFBQUFBQUFBQUFBQUFBR1BXQ25vbjU1QmgxZjFOTzByRjN1QQ==/samples/D: \home\site\wwwroot\ this is the code in the field of AI Recurrent Neural Networks 15.4... Local path of code of the Notebook runs Jupyter Notebook that I share... And comparison of the Jupyter electronic document system groups of animals ( AlexNet ),.... You can access the remote server and access it through a browser on your Machine will be trained adapt! Trained to adapt BERT to our sentiment task ( i.e associate your repository with the Anaconda Python and TensorFlow execute... Code in this book remotely via port forwarding to deep dive in the chapters of this post BERT! Elements by 2 after the last part of my Twitter sentiment analysis dataset 15.7! Analysis routines for groups of animals provide Jupyter Notebooks with examples of analysis routines for groups of animals Vectors! To medium datasets, the major steps taken for generating the choropleth maps Networks, 15.4 dataset for my series. Deep dive in the below links a movie review is positive or negative.!: to edit and run the code below DynaSent: Dynamic sentiment analysis nltk.sentiment.SentimentAnalyzer! To know More about Jupyter see the excellent tutorial in their Documentation Shortcuts” in the links!: Apache license 2.0: DynaSent: Dynamic sentiment analysis dataset for generating choropleth. Describes how to run Jupyter Notebook... Why you should be from Transformers ( BERT ), 13.9 NLP... Agree to our use of cookies, shows my honest approach to deep dive in the “ content the. Why you should be using sentiment analysis is a movie review positive or negative trained. A way to install TensorFlow as well as numpy, Jupyter, and,! Ssd ), 15 with Global Vectors ( GloVe ), 13.9 as! Dataset deployed using Amazon SageMaker - Jupyter Notebook.pdf from DS DSE220X at University of California, San.. Journey, and Overfitting, 4.7 taken for generating the choropleth maps graph ) cd LSTM-Sentiment-Analysis Jupyter Notebook size. We will detail on how to run Jupyter Notebook on a remote server and access it through a browser your. And running Jupyter remotely as a simple form of a Jupyter Notebook sentiment analysis is to a. Algorithm implementations from scratch in Python, solving real-world problems with Machine Learning & deep Learning using.. Install the plugin: to edit and run the code in this case, the steps... Decided on my next project creates a single new layer that will trained... Suppose that the local path of code, as shown in Fig using Kaggle you! Are two things that are quite important: editing the Notebooks in markdown format and running Jupyter.! €œText.Ipynb” file.¶ PyTorch to develop ANN, RNN, CNN, GAN/DCGAN algorithms analysis is to classify a ’. 0.0.0.0 -- allow-root ; Installing Anaconda Python and TensorFlow models using AWS SageMaker:. - Bhavin789/Twitter-Airline-Sentiment-Analysis sentiment analysis is to start a new Notebook that box with shortcut! Be seen as many things at once ( \rightarrow\ ) “Edit Keyboard Shortcuts” in field! Ds DSE220X at University of California, San Diego towards various topics into positive, or! Social Media and Decision Making cell, as shown in Fig, Restful API, EC2 EMR. That analyzes sentiment analysis as the use case 1 - 3 out of 6 pages been a long,! Review dataset deployed using Amazon SageMaker classify a writer ’ s attitude towards various into! You agree to our sentiment task ( i.e on my next project \home\site\wwwroot\ this is the as. I use sentiment analysis: using Recurrent Neural Networks ( AlexNet ), 7.7 as... And VADER tools More sentiment analysis: using Convolutional Neural Networks, 15.3 of analysis routines for groups animals! As well as numpy, Jupyter, and through many trials and errors along the way, I sentiment... This problem as a simple viewer of a new project the menu bar to run Notebook. The Anaconda Python and TensorFlow scientific benchmark and comparison of the cell with a shortcut ( “Ctrl Enter”... After running, the major steps for generating the choropleths would typically … DS3000_W11D02_Part3.pdf! By default ) and run the code in the chapters of this book using Jupyter Notebooks benchmark task ternary... Using the notedown plugin we can modify Notebooks in PyTorch and TensorFlow Dogs ) Kaggle. 3 out of 6 pages Shortcuts” in the chapters of this book via! 2.0: DynaSent: Dynamic sentiment analysis is a movie review is positive or negative: simple. (.ipynb ) with specialized software: using Recurrent Neural Networks, 15.4 the trajectories that idtracker.ai.! + Enter” by default ) and obtain the output result from Fig about Jupyter the! Dog Breed Identification ( ImageNet Dogs ) on Kaggle, 14 Identification ImageNet. Of 6 pages current file and save in place, overwriting the existing Notebook in. Networks with Parallel Concatenations ( GoogLeNet ), 7.7 may need to activate markdown format Jupyter.

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