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SSD | PyTorch

pytorch.org | 4 min read | listed 2 days ago in reddit/pytorch/Retraining Single Shot MultiBox Detector model on a custom data set?

An open source machine learning framework that accelerates the path from research prototyping to production deployment.

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Comprehensive Guide to the Normal Distribution - KDnuggets

www.kdnuggets.com | 5 min read | listed 2 days ago in KDnuggets

Drop in for some tips on how this fundamental statistics concept can improve your data science.

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Market Data and News: A Time Series Analysis - KDnuggets

www.kdnuggets.com | 10 min read | listed 1 day ago in KDnuggets

In this article we introduce a few tools and techniques for studying relationships between the stock market and the news. We explore time series processing, anomaly detection, and an event-based view of the news. We also generate intuitive charts to demonstrate some of these concepts, and share the code behind…

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Custom colour palettes for {ggplot2} | R-bloggers

www.r-bloggers.com | 9 min read | listed 2 days ago in R-bloggers

Choosing which colours to use in a plot is an important design decision. A good choice of colour palette can highlight important aspects of your data, but a poor choice can make it impossible to i...

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How fast can we perform a forward pass?

bounded-regret.ghost.io | 20 min read | listed 2 days ago in DataScienceWeekly.org — Data Science Weekly - Issue 448

Thanks to Hao Zhang, Kayvon Fatahalian, and Jean-Stanislas Denain for helpful discussions and comments. Over the last month, I’ve spent a lot of time trying to answer the following question: How quickly can we perform one forward pass in a transformer model? By a transformer model, I mean BERT,

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Visualizing Filters and Feature Maps in Convolutional Neural Networks using PyTorch

debuggercafe.com | 18 min read | listed 2 days ago in reddit/pytorch/Visualizing Filters and Feature Maps in Convolutional Neural Networks using PyTorch

Learn how to visualize filters and features maps in convolutional neural networks using the ResNet-50 deep learning model.

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Manage AutoML workflows with AWS Step Functions and AutoGluon on Amazon SageMaker | AWS Machine Learning Blog

aws.amazon.com | 7 min read | listed 1 day ago in Amazon AWS AI Blog

Running machine learning (ML) experiments in the cloud can span across many services and components. The ability to structure, automate, and track ML experiments is essential to enable rapid development of ML models. With the latest advancements in the field of automated machine learning (AutoML), namely the area of ML dedicated to the automation of […]

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Analyze and tag assets stored in Veeva Vault PromoMats using Amazon AppFlow and Amazon AI Services | AWS Machine Learning Blog

aws.amazon.com | 17 min read | listed 1 day ago in Amazon AWS AI Blog

In a previous post, we talked about analyzing and tagging assets stored in Veeva Vault PromoMats using Amazon AI services and the Veeva Vault Platform’s APIs. In this post, we explore how to use Amazon AppFlow, a fully managed integration service that enables you to securely transfer data from software as a service (SaaS) applications […]

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Data Engineering - A Journal with Pragmatic Blueprint - Analytics Vidhya

www.analyticsvidhya.com | 6 min read | listed 2 days ago in Analytics Vidhya

In this article, learn about the role of data engineering which is to design the pipeline in a way that we acquire the data without any loss.

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Predict types of machine failures with no-code machine learning using Amazon SageMaker Canvas | AWS Machine Learning Blog

aws.amazon.com | 11 min read | listed 2 days ago in Amazon AWS Machine Learning Blog

Predicting common machine failure types is critical in manufacturing industries. Given a set of characteristics of a product that is tied to a given type of failure, you can develop a model that can predict the failure type when you feed those attributes to a machine learning (ML) model. ML can help with insights, but […]

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Fully Automating Server-side Object Detection Workflows – The Official Blog of BigML.com

blog.bigml.com | 8 min read | listed 2 days ago in The Official Blog of BigMl.com

Continuing with our Object Detection release blog posts series, today, we’ll showcase how to automate the training of the object detection models (and their predictions) that anyone will be a…

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Powershap: A Shapley feature selection method

analyticsindiamag.com | 7 min read | listed 2 days ago in Analytics India Magazine | Artificial Intelligence & Data Science stories

The Shapley value is a game theory solution that explains the impact of each feature on the algorithm by calculating statistical values.

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Hypothesis Testing in Inferential Statistics - Analytics Vidhya

www.analyticsvidhya.com | 7 min read | listed 2 days ago in Analytics Vidhya

In this article, you will learn about hypothesis testing in inferential statistics and we will explain the 5 steps taken to conduct it.

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Getting started with Apache Pig! - Analytics Vidhya

www.analyticsvidhya.com | 12 min read | listed 1 day ago in Analytics Vidhya

In this article, you will learn about the Apache Pig in details and analyze any type of data present in HDFS.

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Farewell, CUDA OOM: Automatic Gradient Accumulation

www.mosaicml.com | 6 min read | listed 2 days ago in reddit/MachineLearning/[P] Farewell, CUDA OOM: Automatic Gradient Accumulation

With automatic gradient accumulation, Composer lets users seamlessly change GPU types and number of GPUs without having to worry about batch size. CUDA out of memory errors are a thing of the past!

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Reverse Engineering Google Colab

dagshub.com | 9 min read | listed 2 days ago in reddit/MachineLearning/[P] Reverse Engineering Google Colab

Take a peek into the internals of Google Colab, and discover how we can bend the rules of Colab a little in order to adapt it to our MLOps workflow

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Filtering numbers quickly with SVE on Amazon Graviton 3 processors – Daniel Lemire's blog

lemire.me | 4 min read | listed 2 days ago in Daniel Lemire's blog

I have had access to Amazon’s latest ARM processors (graviton 3) for a few weeks. To my knowledge, these are the first widely available processors supporting Scalable Vector Extension (SVE). SVE is part of the Single Instruction/Multiple Data paradigm: a single instruction can operate on many values at once. Thus, for example, you may add … Continue reading Filtering numbers quickly with SVE on Amazon Graviton 3 processors

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Spring Security Oauth2 with Keycloak - PKCE Authorization Code Flow

www.analyticsvidhya.com | 7 min read | listed 2 days ago in Analytics Vidhya

In this article, you will learn about spring security with keycloak using proof key code enhanced authorization code flow.

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How to Realize Real-time ML in 15 Minutes with Tecton and Databricks - The Databricks Blog

databricks.com | 6 min read | listed 2 days ago in Databricks

Learn how the right tools can dramatically simplify the challenges bringing real-time ML systems to production.With Tecton and Databricks, you’ll be able to build the MVP for a real-time ML system in minutes, including real-time data processing and online inference.

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Improve ML developer productivity with Weights & Biases: A computer vision example on Amazon SageMaker | AWS Machine Learning Blog

aws.amazon.com | 10 min read | listed 1 day ago in Amazon AWS AI Blog

The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post. As more organizations use deep learning techniques such as computer vision and natural language processing, the machine learning (ML) developer persona needs scalable tooling around experiment tracking, lineage, and […]

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A Python Tutorial for Machine Learning | Python in Plain English

python.plainenglish.io | 5 min read | listed 1 day ago in Machine Learning - Topic feed @ Medium

The quick guide to Machine Learning using Python

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The quality of an RNG depends on the application

www.johndcook.com | 4 min read | listed 2 days ago in Consulting in mathematics, statistics, and scientific computing

Example of an RNG that does really well in one application and fails terribly in another.

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Unpaired Image to Image Translations with Cycle GANs

blog.paperspace.com | 17 min read | listed 2 days ago in Paperspace Blog

In this tutorial, we show how to implement cycle GANs from scratch for image to image translation in TensorFlow using a clever combination of a ResNet generator and Patch GAN discriminator.

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There’s a better way to get your ML test metrics

humanloop.com | 5 min read | listed 2 days ago in reddit/LanguageTechnology/There’s a better way to get your ML test metrics

Machine learning test metrics should always be calculated with credible intervals. Credible intervals give you upper and lower bounds on test performance so you know how big your test needs to be and when to trust your models. Humanloop Active Testing can give you uncertainty bounds on your test metrics and makes this easy.

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Project Scope Management – Process Groups

www.simplilearn.com | 2 min read | listed 1 day ago in Simplilearn

Project Scope management includes the processes that is required to ensure the project. Learn more and improve your PMP exam prep towards achieving PMP

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