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Geometrical Interpretation of Linear Regression in Machine Learning versus Classical Statistics | by Rishabh Raman | Dec, 2023

Demystifying the confusion about Linear Regression Visually and Analytically Image: Linear regression illustration, by Stpasha, via Wikimedia Commons (Public Domain). Original Image Link: https://upload.wikimedia.org/wikipedia/commons/8/87/OLS_geometric_interpretation.svgThe above image represents a geometric interpretation of Ordinary Least Squares (OLS) or Linear Regression (words used interchangeably in classical statistics). Let’s break down what we’re seeing in an intuitive way: Variables…

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Teaching AI to Play Board Games. Using reinforcement learning from… | by Heiko Hotz | Dec, 2023

Using reinforcement learning from scratch to teach a computer to play Tic-Tac-Toe Image by author (created with ChatGPT)It appears that everyone in the AI sector is currently honing their Reinforcement Learning (RL) skills, especially in Q-learning, following the recent rumours about OpenAI’s new AI model, Q* and I’m joining in too. However, rather than speculating…

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How to design an MLOps architecture in AWS? | by Harminder Singh

A guide for developers and architects especially those who are not specialized in machine learning to design an MLOps architecture for their organization Introduction According to Gartner’s findings, only 53% of machine learning (ML) projects progress from proof of concept (POC) to production. Often there is a misalignment between the strategic objectives of the company…

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How Successful Data Scientists Land Tech Jobs in 2024 — A 3-Step Winning Strategy to Job-Hunting | by Khouloud El Alami | Dec, 2023

A Spotify Data Scientist’s guide to developing a job-hunting strategy that can get you offers A snapshot of the survey I conducted on Blind — Image by AuthorI recently ran a survey among data scientists and found out this shocking number — 86% are blindly sending out job applications, and hoping for the best. Hoping…

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Radial Treemaps: Extending Treemaps to Circular Mappings | by Nick Gerend | Dec, 2023

Learn about Radial Treemaps and create your own with Python Radial-Treemap by Nick GerendThe Treemap Concept The “Treemap” was introduced by Ben Shneiderman at the University of Maryland in the early 1990s¹. Simply put, it’s an efficient way of displaying hierarchical data as a set of nested rectangles. Although the concept is simple, the arrangement…

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Convenient Reinforcement Learning With Stable-Baselines3 | by Dr. Robert Kübler | Dec, 2023

Reinforcement learning without the boilerplate code Created by the author with Leonardo Ai.In my previous articles about reinforcement learning, I have shown you how to implement (deep) Q-learning using nothing but a bit of numpy and TensorFlow. While this was an important step towards understanding how these algorithms work under the hood, the code tended…

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TiDE: the ‘embarrassingly’ simple MLP that beats Transformers | by Rafael Guedes | Dec, 2023

A deep exploration of TiDE, its implementation using Darts and a real life use case comparison with DeepAR (a Transformer architecture) As industries continue to evolve, the importance of an accurate forecasting becomes a non-negotiable asset wether you work in e-commerce, healthcare, retail or even in agriculture. The importance of being able to foresee what…

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