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How to Train Ultralytics YOLOv8 models on Your Custom Dataset | 196 classes | Image classification
https://www.reddit.com/r/programming/comments/1px39qt/how_to_train_ultralytics_yolov8_models_on_your/

<!-- SC_OFF -->For anyone studying YOLOv8 image classification on custom datasets, this tutorial walks through how to train an Ultralytics YOLOv8 classification model to recognize 196 different car categories using the Stanford Cars dataset. It explains how the dataset is organized, why YOLOv8-CLS is a good fit for this task, and demonstrates both the full training workflow and how to run predictions on new images. This tutorial is composed of several parts : 🐍Create Conda environment and all the relevant Python libraries. 🔍 Download and prepare the data: We'll start by downloading the images, and preparing the dataset for the train 🛠️ Training: Run the train over our dataset 📊 Testing the Model: Once the model is trained, we'll show you how to test the model using a new and fresh image. Video explanation: https://youtu.be/-QRVPDjfCYc?si=om4-e7PlQAfipee9 Written explanation with code: https://eranfeit.net/yolov8-tutorial-build-a-car-image-classifier/ Link to the post with a code for Medium members : https://medium.com/image-classification-tutorials/yolov8-tutorial-build-a-car-image-classifier-42ce468854a2 If you are a student or beginner in Machine Learning or Computer Vision, this project is a friendly way to move from theory to practice. Eran <!-- SC_ON --> submitted by /u/Feitgemel (https://www.reddit.com/user/Feitgemel)
[link] (https://eranfeit.net/yolov8-tutorial-build-a-car-image-classifier/) [comments] (https://www.reddit.com/r/programming/comments/1px39qt/how_to_train_ultralytics_yolov8_models_on_your/)
C -> Java != Java -> LLM
https://www.reddit.com/r/programming/comments/1pxiyzg/c_java_java_llm/

<!-- SC_OFF -->Many are saying that LLMs are the same kind of transition for programming as assembly -> C or C -> Java. But I don't think that's right because the intermediate artifact hasn't changed in the same way as in those prior transitions. This post explains my thinking. <!-- SC_ON --> submitted by /u/davidkopec (https://www.reddit.com/user/davidkopec)
[link] (https://www.observationalhazard.com/2025/12/c-java-java-llm.html) [comments] (https://www.reddit.com/r/programming/comments/1pxiyzg/c_java_java_llm/)
Rich Hickey: Simplicity is a prerequisite for reliability
https://www.reddit.com/r/programming/comments/1pzfo4r/rich_hickey_simplicity_is_a_prerequisite_for/

<!-- SC_OFF -->Rewatched this recently. Still one of the clearest explanations of why systems fail as complexity accumulates. would like to know how people here apply this in real projects. <!-- SC_ON --> submitted by /u/Digitalunicon (https://www.reddit.com/user/Digitalunicon)
[link] (https://www.infoq.com/presentations/Simple-Made-Easy/) [comments] (https://www.reddit.com/r/programming/comments/1pzfo4r/rich_hickey_simplicity_is_a_prerequisite_for/)
PSA: Be aware when opening "take home challenges" from untrusted recruiters
https://www.reddit.com/r/programming/comments/1pzvo25/psa_be_aware_when_opening_take_home_challenges/

<!-- SC_OFF -->I was recently contacted by linkedIn "recruiter" who's upto no good it seems. After some brief chatting, they asked me to complete a take-home assignment to go ahead with the recruitment process. This is the link to said take home challenge: https://bitbucket.org/brain0xlab/challenge/src/master/ It all seemed a bit suspcious and I wanted to check the repo out before cloning it and opening it myself. This repository contains a vscode auto run task: https://bitbucket.org/brain0xlab/challenge/src/master/.vscode/tasks.json <- This is a HUGE red flag. This task, through several layers of indirection, effectively downloads a stringified obfuscated JS noscript disguised as a json file from this link: https://api.npoint.io/3b0e9f7bfcd85cc9e77d The JSON is downloaded via a "env.js" file downloaded from here (WARNING: malware noscript host): https://vscode-settings-bootstrap[dot]vercel[dot]app/settings/env?flag=306 (replace the dots with actual dots) You'll likely need to use curl -L or something to actually download it. This vscode-settings-bootstrap is likely hosted by the malware creators as this is the website hosting the actual malware stuff primarily. npoint is sort of just a general service. Notice how the env.js file downloads the malware noscript containing json from npoint, extracts the obfuscated js from the cookie field and runs it. I have not managed to gather more information about the malware noscript itself. I know it reads a bunch of system information, reads credentials from filesystem (e.g ssh private keys) and tries to upload them to some domain. I sorta gave up figuring out what domain it is since the noscript does A LOT of useless work to waste cpu cycles and my virtualbox was simply taking too long to get to the meaty part. I have reported the linked in profile and bitbucket repo. TL;DR: Don't open take home challenges and grant it permissions, especially if it contains auto run noscripts... <!-- SC_ON --> submitted by /u/Phantom569 (https://www.reddit.com/user/Phantom569)
[link] (https://bitbucket.org/brain0xlab/challenge/src/master/) [comments] (https://www.reddit.com/r/programming/comments/1pzvo25/psa_be_aware_when_opening_take_home_challenges/)
Frontend development in 2025 - indepth recap
https://www.reddit.com/r/programming/comments/1q0h7k9/frontend_development_in_2025_indepth_recap/

<!-- SC_OFF -->a concise, research-driven recap covering the key shifts in frontend engineering this year—framework evolution, performance metrics (INP), AI tooling impact, accessibility compliance, and infrastructure choices. Read here: https://medium.com/@iammidhul/frontend-development-in-2025-an-in-depth-ecosystem-recap-c38d30ac9b6f?sk=fe167a4ed2fcc3c06f12c2fa596ad77c <!-- SC_ON --> submitted by /u/iammidhul (https://www.reddit.com/user/iammidhul)
[link] (https://medium.com/@iammidhul/frontend-development-in-2025-an-in-depth-ecosystem-recap-c38d30ac9b6f?sk=fe167a4ed2fcc3c06f12c2fa596ad77c) [comments] (https://www.reddit.com/r/programming/comments/1q0h7k9/frontend_development_in_2025_indepth_recap/)