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Deep Learning

This tag is for discussing, sharing articles, and asking questions primarily on deep learning - a subfield of machine learning.

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Why Use RAG? Benefits Over Standard LLMs
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Why Use RAG? Benefits Over Standard LLMs

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2 min read
Understanding AI, Machine Learning, and Deep Learning: A Comprehensive Guide 🚀
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Understanding AI, Machine Learning, and Deep Learning: A Comprehensive Guide 🚀

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4 min read
How Does RAG Improve Large Language Models (LLMs)?
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How Does RAG Improve Large Language Models (LLMs)?

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1 min read
Neural v0.2.1: Macros, Fixes, and PyTorch Training Loop!

Neural v0.2.1: Macros, Fixes, and PyTorch Training Loop!

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3 min read
How Does RAG Differ from Traditional NLP Models?
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How Does RAG Differ from Traditional NLP Models?

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3 min read
What is Retrieval-Augmented Generation (RAG)? A Beginner’s Guide
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What is Retrieval-Augmented Generation (RAG)? A Beginner’s Guide

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2 min read
Implementing PPO for Cartpole-v1
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Implementing PPO for Cartpole-v1

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2 min read
Achieving 1st Place in the VN1 Forecasting Competition with Fine-Tuned Moirai Model

Achieving 1st Place in the VN1 Forecasting Competition with Fine-Tuned Moirai Model

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4 min read
Mean, Variance, and Standard Deviation
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Mean, Variance, and Standard Deviation

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3 min read
Windows 11 Virtual Machine Set Up on Microsoft Azure
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Windows 11 Virtual Machine Set Up on Microsoft Azure

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6 min read
Area Under the Curve
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Area Under the Curve

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3 min read
Transformer-Squared: The Next Evolution in Self-Adaptive LLMs
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Transformer-Squared: The Next Evolution in Self-Adaptive LLMs

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5 min read
Mastering Machine Learning :Why One-Hot Encode Data in Machine Learning?

Mastering Machine Learning :Why One-Hot Encode Data in Machine Learning?

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2 min read
Predicting Protein Secondary Structures with Machine Learning
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Predicting Protein Secondary Structures with Machine Learning

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3 min read
Part 1: Detecting Alzheimer’s with EEG and Deep Learning – Theory, Motivation, and Preprocessing
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Part 1: Detecting Alzheimer’s with EEG and Deep Learning – Theory, Motivation, and Preprocessing

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4 min read
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