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Learnings from a Machine Learning Engineer — Part 4: The Model

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 7 min read · 4 days ago — Photo by Hal Gatewood on Unsplash In this last part of my series, I will share what I have learned on selecting a model for image classification and how to fine tune that model. I will also show how you can leverage the model to accelerate your labelling

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Learnings from a Machine Learning Engineer — Part 3: The Evaluation

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 11 min read · 4 days ago — Photo by FlyD on Unsplash In this third part of my series, I will explore the evaluation process which is a critical piece that will lead to a cleaner data set and elevate your model performance. We will see the difference between evaluation of a trained model (one

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Learnings from a Machine Learning Engineer — Part 2: The Data Sets

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 8 min read · 4 days ago — Photo by Conny Schneider on Unsplash In Part 1, we discussed the importance of collecting good image data and assigning proper labels for your image classification project to be successful. Also, we talked about classes and sub-classes of your data. These may seem pretty straight forward concepts, but

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Top 3 Questions to Ask in Near Real-Time Data Solutions

Questions that guide architectural decisions to balance functional requirements like most frequent queries with non-functional requirements such as latency and scalability. Shawn Shi · Follow Published in Towards Data Science · 16 min read · 6 hours ago — Image by author. Icons from flaticon.com. Introduction Would you agree that our life is surrounded by technology nowadays? Technology has changed our lifestyle in all kinds of ways in the past decade. Behind the scene, data

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The Data Analyst Every CEO Wants

Data Analyst is probably the most underrated job in the data industry Benoit Pimpaud · Follow Published in Towards Data Science · 7 min read · Apr 2, 2024 — Credits Unsplash With only self-service as the last level in the analytics game, we often underestimate how much an ad-hoc analysis made by someone who understands business AND understands data can be valuable. I got the chance to work with a few in my previous

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A 12-step visual guide to understanding NeRF (Representing Scenes as Neural Radiance Fields)

NeRF overview — Image by Author A basic understanding of NeRF’s workings through visual representations Aqeel Anwar · Follow Published in Towards Data Science · 10 min read · 3 days ago — Who should read this article? This article aims to provide a basic beginner level understanding of NeRF’s workings through visual representations. While various blogs offer detailed explanations of NeRF, these are often geared toward readers with a strong technical background in volume

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Basics of GANs & SMOTE for Data Augmentation

GANs and SMOTE explained through bartending: Data Science for Machine Learning Series (1) Sunghyun Ahn · Follow Published in Towards Data Science · 12 min read · 1 day ago — SMOTE Technique Mechanism If you are not a paid member on Medium, I make my stories available for free: Friends link Personally, it feels like data is treated as the new oil of the digital age. This feels especially true with the boom in

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Water Cooler Small Talk: Benford’s Law

STATISTICS A look into the strange first digit distribution of naturally occurring datasets Maria Mouschoutzi, PhD · Follow Published in Towards Data Science · 9 min read · 8 hours ago — Image created by the author using GPT-4 / All other images created by the author unless specified otherwise Ever heard a co-worker confidently declaring something like “The longer I lose at roulette, the closer I am to winning?” Or had a boss that

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Learnings from a Machine Learning Engineer — Part 1: The Data

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 11 min read · 3 days ago — Photo by Joshua Sortino on Unsplash It is said that in order for a machine learning model to be successful, you need to have good data. While this is true (and pretty much obvious), it is extremely difficult to define, build, and sustain good data. Let me share

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Qubits Explained: Everything You Need to Know

A deep dive into the building block of quantum computers. Sara A. Metwalli · Follow Published in Towards Data Science · 10 min read · 9 hours ago — Photo by Google DeepMind on Unsplash In honor of the International Year of Quantum Technology, I plan to write as many articles as possible about different aspects of the quantum field. However, to discuss deeper and more technical topics, I first need to explain the basics

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