Catégorie : Notes
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Applying Context Aware Spell Checking in Spark NLP
Applying Context Aware Spell Checking in Spark NLP which is scalable, extensible, and highly accurate! Btw you can extend it with your own training to add support for more languages or specific domains. Blogpost https://medium.com/spark-nlp/applying-context-aware-spell-checking-in-spark-nlp-3c29c46963bc GitHub https://github.com/JohnSnowLabs/spark-nlp JohnSnowLabs/spark-nlp: State of the Art Natural Language Processing – GitHub Spark NLP: State of the Art Natural Language…
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This repository implements the Matching Networks architecture (Vinyals et al., 2016) in pytorch and applies it to a Language Modelling task.
This repository implements the Matching Networks architecture (Vinyals et al., 2016) in pytorch and applies it to a Language Modelling task. https://github.com/adriangonz/statistical-nlp-17
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GitHub – AkariAsai/learning_to_retrieve_reasoning_paths: The official implementation of ICLR 2020, « Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering ».
https://github.com/AkariAsai/learning_to_retrieve_reasoning_paths
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turbo_transformers: a fast and user-friendly runtime for transformer inference on CPU and GPU
Transformer is the most critical alogrithm innovation in the NLP field in recent years. It brings higher model accuracy while introduces more calculations. The efficient deployment of online Transformer-based services faces enormous challenges. In order to make the costly Transformer online service more efficient, the WeChat AI open-sourced a Transformer inference acceleration tool called TurboTransformers,…
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An overview of gradient descent optimization algorithms
https://ruder.io/optimizing-gradient-descent/ An overview of gradient descent optimization algorithms Gradient descent is the preferred way to optimize neural networks and many other machine learning algorithms but is often used as a black box. This post explores how many of the most popular gradient-based optimization algorithms such as Momentum, Adagrad, and Adam actually work. ruder.io
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5 Obscure Python Libraries Every Data Scientist Should Know | by Andre Ye | Jul, 2020 | Towards Data Science
https://towardsdatascience.com/5-obscure-python-libraries-every-data-scientist-should-know-3651bf5d3be3
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GitHub – bjascob/LemmInflect: A python module for English lemmatization and inflection.
https://github.com/bjascob/LemmInflect
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GitHub – iterative/cml: ♾️ CML – Continuous Machine Learning | CI/CD for ML
https://github.com/iterative/cml
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GitHub – Palashio/libra: Fully automated machine learning in one-liners.
https://github.com/Palashio/libra
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Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
https://github.com/google-research/torchsde GitHub – google-research/torchsde: Differentiable SDE solvers with GPU support and efficient sensitivity analysis. Examples. demo.ipynb in the examples folder is a short guide on how one may use the codebase for solving SDEs without considering gradient computation. It covers subtle points such as fixing the randomness in the solver and the consequence of noise…
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DeepSinger: Singing Voice Synthesis with Data Mined From the Web – SpeechResearch
https://speechresearch.github.io/deepsinger/ DeepSinger: Singing Voice Synthesis with Data Mined From the Web – SpeechResearch DeepSinger: Singing Voice Synthesis with Data Mined From the Web Authors. Yi Ren* (Zhejiang University) rayeren@zju.edu.cn Xu Tan* (Microsoft Research Asia) xuta@microsoft.com Tao Qin (Microsoft Research Asia) taoqin@microsoft.com Jian Luan (Microsoft STCA Xiaoice) jianluan@microsoft.com Zhou Zhao (Zhejiang University) zhaozhou@zju.edu.cn Tie-Yan Liu (Microsoft…
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Overview — Elyra 1.0.0.dev0 documentation
https://elyra.readthedocs.io/en/latest/getting_started/overview.html https://github.com/elyra-ai/elyra
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GitHub – dask/dask-examples: Easy-to-run example notebooks for Dask
https://github.com/dask/dask-examples
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GitHub – graphbrain/graphbrain: Language, Knowledge, Cognition
https://github.com/graphbrain/graphbrain
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NLP News Cypher | 07.12.20. Negative Ghost Rider, the Pattern is… | by Quantum Stat | To wards AI — Multidisciplinary Science Journal | Jul, 2020 | Medium
https://medium.com/towards-artificial-intelligence/nlp-news-cypher-07-12-20-fdede056694d
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The Super Duper NLP Repo
https://notebooks.quantumstat.com/
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The Big Bad NLP Database – Quantum Stat
https://datasets.quantumstat.com/
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Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention | Papers With Code
https://paperswithcode.com/paper/transformers-are-rnns-fast-autoregressive
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DeepMind Explores Deep RL for Brain and Behaviour Research | Synced
https://syncedreview.com/2020/07/10/deepmind-explores-deep-rl-for-brain-and-behaviour-research/
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Five Machine Learning Paradoxes that will Change the Way You Think About Data | by Jesus Rodriguez | DataSeries | Jul, 2020 | Medium
https://medium.com/dataseries/five-machine-learning-paradoxes-that-will-change-the-way-you-think-about-data-3b82513482b8
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GitHub – JaidedAI/EasyOCR: Ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai
https://github.com/JaidedAI/EasyOCR
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The Open Source Technologies Behind One of the Biggest Language Models in History
https://medium.com/dataseries/the-open-source-technologies-behind-one-of-the-biggest-language-models-in-history-5757442b0bb3 The Open Source Technologies Behind One of the Biggest Language Models in History ZeRO and DeepSpeed are powering Microsoft’s Turing-NLG which is considered one of the largest natural language models in the history of AI. medium.com
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The Methods Corpus | Papers With Code
https://paperswithcode.com/methods The Methods Corpus | Papers With Code 735 methods • 25561 papers with code. Get the latest machine learning methods with code. Browse our catalogue of tasks and access state-of-the-art solutions. paperswithcode.com
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https://nanonets.com/blog/table-extraction-deep-learning/
https://nanonets.com/blog/table-extraction-deep-learning/
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How Azure.com operates on Azure
https://azure.microsoft.com/en-us/blog/how-azurecom-operates-on-azure-part-2-technology-and-architecture/ How Azure.com operates on Azure part 2: Technology and architecture | Azure Blog and Updates | Microsoft Azure When you’re the company that builds the cloud platforms used by millions of people, your own cloud content needs be served up fast. Azure.com—a complex, cloud-based application that serves millions of people every day—is built entirely…
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TaBert
https://ai.facebook.com/blog/tabert-a-new-model-for-understanding-queries-over-tabular-data/
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From Jupyter Notebook to Azure Web App in 5 Easy Steps
https://medium.com/microsoftazure/from-jupyter-notebook-to-azure-web-app-in-5-easy-steps-2783f8fd847d From Jupyter Notebook to Azure Web App in 5 Easy Steps You have been exploring data in Jupyter Notebook and would like to share the insights. Some of your plots have filters, interactivity. You… medium.com
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How You Should Read Research Papers According To Andrew Ng
https://towardsdatascience.com/how-you-should-read-research-papers-according-to-andrew-ng-stanford-deep-learning-lectures-98ecbd3ccfb3 How You Should Read Research Papers According To Andrew Ng (Stanford Deep Learning Lectures) “Wisdom is not a product of schooling but of the lifelong attempt to acquire it.” — Albert Einstein. Introduction. The ability to understand information produced by the individuals at the cutting edge of research within Artificial Intelligence and the Machine…
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MLflow – A platform for the machine learning lifecycle
https://mlflow.org/ MLflow – A platform for the machine learning lifecycle | MLflow MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. mlflow.org
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Are Better Machine Training Approaches Ahead?
https://semiengineering.com/are-better-machine-training-approaches-ahead Are Better Machine Training Approaches Ahead? We live in a time of unparalleled use of machine learning (ML), but it relies on one approach to training the models that are implemented in artificial neural networks (ANNs) — so named because they’re not neuromorphic.But other training approaches, some of which are more biomimetic than others,…
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Logistic Regression in Machine Learning with Python
https://medium.com/@amankharwal/logistic-regression-in-machine-learning-with-python-da302d82cc3d Logistic Regression in Machine Learning with Python One of the best things about the scikit-learn library in python is that it provides four steps modeling patterns that make it easy for the… medium.com
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Deep Learning Models for Automatic Summarization – Towards Data Science
https://towardsdatascience.com/deep-learning-models-for-automatic-summarization-4c2b89f2a9ea Deep Learning Models for Automatic Summarization – Towards Data Science Figure 1: Basic Seq2Seq encoder-decoder architecture with attention.The x_i are the input token embeddings, the a_i^t are the attention weights at step t, the h_i are the context vectors, h^t is the sentence embedding at step t obtained by weighting the context vectors with…
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GitHub – QData/TextAttack: TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP
TextAttack is a library for running adversarial attacks against natural language processing (NLP) models. TextAttack builds attacks from four components: a search method, goal function, transformation, and a set of constraints. https://github.com/QData/TextAttack https://arxiv.org/abs/2005.05909
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Jupyter to Medium
https://www.dexplo.org/jupyter_to_medium/
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The 3 Ways To Compute Feature Importance in the Random Forest | MLJAR
https://mljar.com/blog/feature-importance-in-random-forest/
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8 Fun Machine Learning Projects for Beginners
https://elitedatascience.com/machine-learning-projects-for-beginners 8 Fun Machine Learning Projects for Beginners Examples of machine learning projects for beginners you could try include… Anomaly detection… Map the distribution of emails sent and received by hour and try to detect abnormal behavior leading up to the public scandal. Social network analysis… Build network graph models between employees to find key…
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Using GitHub Actions for MLOps & Data Science
https://github.blog/2020-06-17-using-github-actions-for-mlops-data-science/ Using GitHub Actions for MLOps & Data Science – The GitHub Blog Background. Machine Learning Operations (or MLOps) enables Data Scientists to work in a more collaborative fashion, by providing testing, lineage, versioning, and historical information in an automated way. Because the landscape of MLOps is nascent, data scientists are often forced to implement…
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A deep reinforcement learning framework to identify key players in complex networks
https://techxplore.com/news/2020-06-deep-framework-key-players-complex.html A deep reinforcement learning framework to identify key players in complex networks Network science is an academic field that aims to unveil the structure and dynamics behind networks, such as telecommunication, computer, biological and social networks. One of the fundamental problems that network scientists have been trying to solve in recent years entails identifying…
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OpenAI’s GPT-3 Language Model: A Technical Overview
https://lambdalabs.com/blog/demystifying-gpt-3/?utm_source=newsletter&utm_medium=email&utm_campaign=Andriy_Burkov_AI_newsletter
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Introducing dotnet-monitor, an experimental tool | .NET Blog
https://devblogs.microsoft.com/dotnet/introducing-dotnet-monitor/
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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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Bert: Step by step by Hugging face – The Startup – Medium
https://medium.com/swlh/bert-step-by-step-b7ff47fcfbe
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Introducing GitHub Super Linter: one linter to rule them all – The GitHub Blog
https://github.blog/2020-06-18-introducing-github-super-linter-one-linter-to-rule-them-all/
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Traitement automatique du langage naturel | Coursera
https://www.coursera.org/specializations/natural-language-processing?utm_source=deeplearningai&utm_medium=institutions&utm_content=NLP_0617_ng
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https://medium.com/dataseries/meta-learning-teaches-us-that-the-brain-has-a-unique-learning-advantage-over-ai-and-it-has-to-do-f6bed5a825f6
https://medium.com/dataseries/meta-learning-teaches-us-that-the-brain-has-a-unique-learning-advantage-over-ai-and-it-has-to-do-f6bed5a825f6
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RubberDuck, CMS préféré des agences
https://rubberduckcms.com/fr
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The Johnson-Lindenstrauss lemma & Linformer | Teven Le Scao
https://tevenlescao.github.io/blog/fastpages/jupyter/2020/06/18/JL-Lemma-+-Linformer.html
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Open source data analytics processing
https://cloudblog-withgoogle-com.cdn.ampproject.org/c/s/cloudblog.withgoogle.com/products/data-analytics/introducing-spark-3-and-hadoop-3-on-dataproc-image-version-2-0/amp/