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State of Machine Learning Survey Results Part Two

ODSC - Open Data Science

Recently, we posted the first article recapping our recent machine learning survey. There, we talked about some of the results, such as what programming languages machine learning practitioners use, what frameworks they use, and what areas of the field they’re interested in. As the chart shows, two major themes emerged.

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Machine Learning with MATLAB and Amazon SageMaker

Flipboard

MATLAB   is a popular programming tool for a wide range of applications, such as data processing, parallel computing, automation, simulation, machine learning, and artificial intelligence. Part 1: Data preparation & feature extraction The first step in any machine learning project is to prepare your data.

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Top 10 Machine Learning (ML) Tools for Developers in 2023

Towards AI

Last Updated on June 27, 2023 by Editorial Team Source: Unsplash This piece dives into the top machine learning developer tools being used by developers — start building! In the rapidly expanding field of artificial intelligence (AI), machine learning tools play an instrumental role.

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Demystifying Data Preparation for Large Language Models (LLMs)

Flipboard

In the rapidly evolving landscape of artificial intelligence, large language models (LLMs) have emerged as a transformative force for modern enterprises. These powerful models, exemplified by GPT-4 and its predecessors, offer the potential to drive innovation, enhance productivity, and fuel business growth.

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Unlocking the Power of AI with Implemented Machine Learning Ops Projects

Becoming Human

Machine learning operations, or MLOps, are the set of practices and tools that aim to streamline and automate the machine learning lifecycle. It covers everything from data preparation and model training to deployment, monitoring, and maintenance. What are MLOps Projects?

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Empower your career – Discover the 10 essential skills to excel as a data scientist in 2023

Data Science Dojo

These skills include programming languages such as Python and R, statistics and probability, machine learning, data visualization, and data modeling. This includes sourcing, gathering, arranging, processing, and modeling data, as well as being able to analyze large volumes of structured or unstructured data.

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AI annotation jobs are on the rise

Dataconomy

In simple terms, data annotation is the process of labeling various types of content, including text, audio, images, and videos. These labels provide crucial context for machine learning models, enabling them to make informed decisions and predictions.