Catégorie : Notes
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Why 90 percent of all machine learning models never make it into production
https://towardsdatascience.com/why-90-percent-of-all-machine-learning-models-never-make-it-into-production-ce7e250d5a4a Why 90 percent of all machine learning models never make it into production | by Rhea Moutafis | Nov, 2020 | Towards Data Science C orporations are going through rough times. And I’m not talking about the pandemic and the stock market volatility. The times are uncertain, and having to make customer experiences more…
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GitHub – alihussainia/openvino-colab: OpenVINO Edge AI Applications deployment on Google Colaboratory
https://github.com/alihussainia/openvino-colab
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AI Expert Roadmap
https://github.com/AMAI-GmbH/AI-Expert-Roadmap/ GitHub – AMAI-GmbH/AI-Expert-Roadmap: Roadmap to becoming an Artificial Intelligence Expert in 2020 i.am.ai AI Expert Roadmap. Roadmap to becoming an Artificial Intelligence Expert in 2020. Below you find a set of charts demonstrating the paths that you can take and the technologies that you would want to adopt in order to become a data…
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Vowpal Wabbit
https://github.com/VowpalWabbit/vowpal_wabbit/wiki VowpalWabbit/vowpal_wabbit Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive lea… github.com
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Pandas_ui
https://medium.com/@arunnbaba/pandas-ui-87316a4e19c7 https://github.com/arunnbaba/pandas_ui GitHub – arunnbaba/pandas_ui: pandas_ui helps you wrangle & explore your data and create custom visualizations without digging through StackOverflow. All inside your Jupyter Notebook ( alternative to Bamboolib ). pandas_ui helps you wrangle & explore your data and create custom visualizations without digging through StackOverflow. All inside your Jupyter Notebook ( alternative to…
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Hugging Face Transformers – Get started !
https://www.kaggle.com/funtowiczmo/hugging-face-transformers-get-started Hugging Face Transformers – Get started ! | Kaggle We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. www.kaggle.com
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Hedonometer
https://hedonometer.org/papers.html
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man-group/dtale: Visualizer for pandas data structures
https://github.com/man-group/dtale
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An Ultimate Cheat Sheet for Data Visualization in Pandas
https://towardsdatascience.com/an-ultimate-cheat-sheet-for-data-visualization-in-pandas-4010e1b16b5c
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Recommendation system in depth tutorial with python for netflix using collaborative filtering
https://medium.com/towards-artificial-intelligence/recommendation-system-in-depth-tutorial-with-python-for-netflix-using-collaborative-filtering-533ff8a0e444
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Python Data Science Handbook
This website contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks. The text is released under the CC-BY-NC-ND license, and code is released under the MIT license. If you find this content useful, please consider supporting the work by…
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A gentle introduction to web scraping with python
https://towardsdatascience.com/a-gentle-introduction-to-web-scraping-with-python-b914a64b2fb8
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PerceptiLabs
https://github.com/PerceptiLabs/PerceptiLabs An intuitive way to build models PerceptiLabs is a dataflow driven, visual API for TensorFlow that enables data scientists to work more efficiently with machine learning models and to gain more insight into their models. It wraps low-level TensorFlow code to create visual components, which allows users to visualize the model architecture as the…
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AI has cracked a key mathematical puzzle for understanding our world
https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2020/10/30/1011435/ai-fourier-neural-network-cracks-navier-stokes-and-partial-differential-equations/amp/
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An introduction to transfer learning in NLP and HuggingFace with Thomas Wolf – YouTube
https://m.youtube.com/watch?v=t86G11tfVNw
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facebookresearch/SentAugment: SentAugment is a data augmentation technique for NLP that retrieves similar sentences from a large bank of sentences. It can be used in combination with self-training and knowledge-distillation, or for retrieving paraphrases.
https://github.com/facebookresearch/SentAugment
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KEDA | Kubernetes Event-driven Autoscaling
https://keda.sh/
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heartexlabs/awesome-data-labeling: A curated list of awesome data labeling tools
https://github.com/heartexlabs/awesome-data-labeling
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Deep Learning or Machine Learning?
What led us to Deep Learning (DL)? Why can’t Machine Learning (ML) work well on text, image, and speech data? Why are Neural Networks so powerful? What is this generalizability that people talk about? In this blog we will answer all these questions. At the end of the blog, the reader will have a complete…
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mT5: Multilingual T5
Multilingual T5 (mT5) is a massively multilingual pretrained text-to-text transformer model, trained following a similar recipe as T5. This repo can be used to reproduce the experiments in the mT5 paper. https://github.com/google-research/multilingual-t5
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Add External Data to Your Pandas Dataframe with a One-Liner | by Jack Shepherd | Oct, 2020 | Towards Data Science
https://towardsdatascience.com/add-external-data-to-your-pandas-dataframe-with-a-one-liner-f060f80daaa4
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27 October, 2020 16:57
https://github.com/pytorch/pytorch/releases/tag/v1.7.0
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SpaCy 3.0
https://explosion.ai/blog/spacy-v3-nightly
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lucidrains/performer-pytorch: An implementation of Performer, a linear attention-based transformer, in Pytorch
https://github.com/lucidrains/performer-pytorch
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EleutherAI/The-Pile
https://github.com/EleutherAI/The-Pile
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google-research/vision_transformer
https://github.com/google-research/vision_transformer
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The Roadmap of Mathematics for Deep Learning | by Tivadar Danka | Oct, 2020 | Towards Data Science
https://towardsdatascience.com/the-roadmap-of-mathematics-for-deep-learning-357b3db8569b
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man-group/notebooker: Productionise your Jupyter Notebooks as easily as you wrote them.
https://github.com/man-group/notebooker
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Learning to Summarize with Human Feedback
https://openai.com/blog/learning-to-summarize-with-human-feedback/
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How to extract Key-Value pairs from Documents using deep learning
https://nanonets-com.cdn.ampproject.org/v/s/nanonets.com/blog/key-value-pair-extraction-from-documents-using-ocr-and-deep-learning/amp/?usqp=mq331AQFKAGwASA%3D&_js_v=0.1#aoh=16033936690115&referrer=https://www.google.com&_tf=From%20%251$s&share=https://nanonets.com/blog/key-value-pair-extraction-from-documents-using-ocr-and-deep-learning/ GitHub – zzzDavid/ICDAR-2019-SROIE: ICDAR 2019 Robust Reading Challenge on Scanned Receipts OCR and Information Extraction ICDAR 2019 Robust Reading Challenge on Scanned Receipts OCR and Information Extraction. Background. This repository is our team’s solution of 2019 ICDAR-SROIE competition. As the name suggests, this competition is mainly about Optical Character Recognition and information extraction: github.com
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21 October, 2020 07:23
https://azure.microsoft.com/en-us/updates/azure-cognitive-services-translator-canadian-french-language-text-translation-now-available/
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2010.10442 BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search
https://arxiv.org/abs/2010.10442
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e-commerce-search/bert2dnn: Large Scale BERT Distillation
https://github.com/e-commerce-search/bert2dnn
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adamerose/pandasgui: A GUI for Pandas DataFrames
https://github.com/adamerose/pandasgui
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How to create and deploy a model card in the cloud with Scikit-Learn
How to create and deploy a model card in the cloud with Scikit-Learn https://cloud.google.com/blog/products/ai-machine-learning/create-a-model-card-with-scikit-learn
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20 October, 2020 15:04
https://github.com/pytorch/fairseq/tree/master/examples/m2m_100
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Why No-Code and Low-Code Software Is the Industry Disrupter You Should Pay Attention To | Inc.com
https://www.inc.com/soren-kaplan/why-no-code-low-code-software-is-industry-disruptor-you-should-pay-attention-to.html
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Find Code for Research Papers – CatalyzeX
https://chrome.google.com/webstore/detail/find-code-for-research-pa/aikkeehnlfpamidigaffhfmgbkdeheil
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Spark and Docker: Your Spark development cycle just got 10x faster !
https://www.datamechanics.co/blog-post/spark-and-docker-your-spark-development-cycle-just-got-ten-times-faster Spark and Docker: Your Spark development cycle just got 10x faster ! – Data Mechanics Blog Native support for Docker is in fact one of the main reasons companies choose to deploy Spark on top of Kubernetes instead of YARN. In this article, we will illustrate the benefits of Docker for Apache Spark by…
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How to Build a Scalable Data Analytics Pipeline
https://www.freecodecamp.org/news/scalable-data-analytics-pipeline/ How to Build a Scalable Data Analytics Pipeline As the data keeps growing in volume the data analytics pipelines have to be scalable to adapt the rate of change. And for this reason, choosing to set up a the pipeline in cloud makes perfect sense (since cloud offers on-demand scalability and flexibility). In this…
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ML Deployment Decision Tree
https://pakodas.substack.com/p/ml-deployment-decision-tree ML Deployment Decision Tree Choose the right tool for your job pakodas.substack.com
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LXMERT Demo.ipynb – Colaboratory
https://colab.research.google.com/drive/18TyuMfZYlgQ_nXo-tr8LCnzUaoX0KS-h?usp=sharing
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14 October, 2020 22:06
https://www.machinelearningplus.com/nlp/topic-modeling-visualization-how-to-present-results-lda-models/ Topic modeling visualization – How to present results of LDA model? | ML+ – Machine Learning Plus In this post, we discuss techniques to visualize the output and results from topic model (LDA) based on the gensim package.. Topic modeling visualization – How to present the results of LDA models? www.machinelearningplus.com
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GitHub CLI 1.0 is now available
https://github.blog/2020-09-17-github-cli-1-0-is-now-available/ GitHub CLI 1.0 is now available – The GitHub Blog GitHub CLI brings GitHub to your terminal. It reduces context switching, helps you focus, and enables you to more easily script and create your own workflows. Earlier this year, we announced the beta of GitHub github.blog
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Implementation of abstractive summarization
https://github.com/JRC1995/Abstractive-Summarization GitHub – JRC1995/Abstractive-Summarization: Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention. Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention. – JRC1995/Abstractive-Summarization github.com
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Reading list for Awesome Sentiment Analysis papers
https://github.com/declare-lab/awesome-sentiment-analysis GitHub – declare-lab/awesome-sentiment-analysis: Reading list for Awesome Sentiment Analysis papers Reading list for Awesome Sentiment Analysis papers. Sentiment analysis as a field has come a long way since it was first introduced as a task nearly 20 years ago. github.com
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Recommendation system tutorial with python
https://medium.com/towards-artificial-intelligence/recommendation-system-in-depth-tutorial-with-python-for-netflix-using-collaborative-filtering-533ff8a0e444
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What I learned from looking at 200 machine learning tools
https://huyenchip.com/2020/06/22/mlops.html
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