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Top 7 Data Science, Large Language Model, and AI Blogs of 2024

Data Science Dojo

In this blog, we will explore the top 7 LLM, data science, and AI blogs of 2024 that have been instrumental in disseminating detailed and updated information in these dynamic fields. To keep up with these rapid developments, it’s crucial to stay informed through reliable and insightful sources.

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Predicting the 2024 U.S. Presidential Election Winner Using Machine Learning

Towards AI

Model Fitting and Training: Various ML models trained on sub-patterns in data. Data Preparation (Synthetic Data) Generating a Dataset Synthetic data constituting age, education, income, political alignment, media consumption, and the target variable-party affiliation will be generated in the same way as real-world voting behaviour.

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

This session covers the technical process, from data preparation to model customization techniques, training strategies, deployment considerations, and post-customization evaluation. Explore how this powerful tool streamlines the entire ML lifecycle, from data preparation to model deployment.

AWS 101
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Why There’s No Better Time to Learn LLM Development

Towards AI

And if you purchased the first edition (prior to October 2024), you’re eligible for an additional discount. A major addition to the book is a brand-new chapter titled Indexes, Retrievers, and Data Preparation. Indexes, Retrievers, and Data Preparation are the foundational components of a RAG pipeline. What’s New?

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2024 Mexican Grand Prix: Formula 1 Prediction Challenge Results

Ocean Protocol

Introduction The Formula 1 Prediction Challenge: 2024 Mexican Grand Prix brought together data scientists to tackle one of the most dynamic aspects of racing — pit stop strategies. This competition emphasized leveraging analytics in one of the world’s fastest and most data-intensive sports.

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Implementing Approximate Nearest Neighbor Search with KD-Trees

PyImageSearch

Figure 1: Example of a 2-dimensional KD-tree (source: Warnasooriya, Medium , 2024 ). We will start by setting up libraries and data preparation. Setup and Data Preparation For implementing a similar word search, we will use the gensim library for loading pre-trained word embeddings vector. What's next? Thakur, eds.,

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Data4ML Preparation Guidelines (Beyond The Basics)

Towards AI

Last Updated on November 9, 2024 by Editorial Team Author(s): Houssem Ben Braiek Originally published on Towards AI. Data preparation isn’t just a part of the ML engineering process — it’s the heart of it. This member-only story is on us. Upgrade to access all of Medium.

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