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Community Spotlight: Brett Mullins

DrivenData Labs

My research focuses on differential privacy and explainable machine learning but extends to other areas where applying formal models brings new ideas to the table. How did you get started in data science? Like many data scientists in the 2010s, I stumbled my way into the field. I'm currently getting set up on a Framework 13.

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Accelerating scope 3 emissions accounting: LLMs to the rescue

IBM Journey to AI blog

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

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Modular functions design for Advanced Driver Assistance Systems (ADAS) on AWS

AWS Machine Learning Blog

These systems require petabytes of data and thousands of compute units (vCPUs and GPUs) to train. End-to-end training – This approach involves training a DNN model that takes raw sensor data as input and outputs the driving command. LiDAR – Expensive devices providing data about the surroundings as a 3D point cloud.

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Unleashing the Power of Applied Text Mining in Python: Revolutionize Your Data Analysis

Pickl AI

The surge of digitization and its growing penetration across the industry spectrum has increased the relevance of text mining in Data Science. Text mining is primarily a technique in the field of Data Science that encompasses the extraction of meaningful insights and information from unstructured textual data.

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AI2 and Microsoft use satellite images plus artificial intelligence to monitor the planet

Flipboard

Satlas’ AI modeling software improves satellite image resolution by a factor of four. The Allen Institute for AI, also known as AI2, recently rolled out Satlas , a new software platform for exploring global geospatial data generated from satellite imagery. Training the model was no easy task. meters per pixel.

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How to tackle lack of data: an overview on transfer learning

Data Science Blog

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

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Natural Language Processing (NLP) Concepts With NLTK

Heartbeat

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk Many data we analyze as data scientists consist of a corpus of human-readable text. We can either: Tokenize by word.