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Rust Burn Library for Deep Learning

KDnuggets

A new deep learning framework built entirely in Rust that aims to balance flexibility, performance, and ease of use for researchers, ML engineers, and developers.

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PyTorch vs TensorFlow: Which is Better for Deep Learning?

Analytics Vidhya

Introduction Efficient ML models and frameworks for building or even deploying are the need of the hour after the advent of Machine Learning (ML) and Artificial Intelligence (AI) in various sectors. Although there are several frameworks, PyTorch and TensorFlow emerge as the most famous and commonly used ones.

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Introduction to Apple’s Core ML 3 – Build Deep Learning Models for the iPhone (with code)

Analytics Vidhya

Overview Apple’s Core ML 3 is a perfect segway for developers and programmers to get into the AI ecosystem You can build machine learning. The post Introduction to Apple’s Core ML 3 – Build Deep Learning Models for the iPhone (with code) appeared first on Analytics Vidhya.

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Artificial Intelligence Vs Machine Learning Vs Deep Learning: What exactly is the difference ?

Analytics Vidhya

Artificial Intelligence, Machine Learning and, Deep Learning are the buzzwords of. The post Artificial Intelligence Vs Machine Learning Vs Deep Learning: What exactly is the difference ? ArticleVideo Book This article was published as a part of the Data Science Blogathon.

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Hydra Configs for Deep Learning Experiments

KDnuggets

This brief guide illustrates how to use the Hydra library for ML experiments, especially in the case of deep learning-related tasks, and why you need this tool to make your workflow easier.

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What Comes After HDF5? Seeking a Data Storage Format for Deep Learning

KDnuggets

But this format is not optimized for deep learning work. This article suggests what kind of ML native data format should be to truly serve the needs of modern data scientists. In this article we are discussing that HDF5 is one of the most popular and reliable formats for non-tabular, numerical data.

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From Google Colab to a Ploomber Pipeline: ML at Scale with GPUs

KDnuggets

In this short blog, we’ll review the process of taking a POC data science pipeline (ML/Deep learning/NLP) that was conducted on Google Colab, and transforming it into a pipeline that can run parallel at scale and works with Git so the team can collaborate on.

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