Stable Face-Mask Detection Using Adapted Eye Cascader
Author(s): Jan Werth Originally published on Towards AI. Photo by Victor Freitas on Unsplash Table of content Introduction Prerequisite Eye Detection via Cascaders– Cascaders– Scalefactor and Min_Neighbour Find Matching eye-pairs– Matching eyes step by step with code– Less than three eyes– Draw …
Top Important Computer Vision Papers for the Week from 24/06 to 30/06
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Computer Vision Research Every week, researchers from top research labs, companies, and universities publish exciting breakthroughs in various topics such as diffusion models, vision language models, image editing and generation, …
The 7 Most Important Skill Sets for ML Engineers
Author(s): Boris Meinardus Originally published on Towards AI. What are the most important skills for an ML Engineer? Well, I asked ML engineers at all these companies to share what they consider the top skills… And I’m telling you, there were a …
Preventing Injuries and Improving Performance in Sports with Machine Learning
Author(s): Eera Bhatt Originally published on Towards AI. That’s right, I was inspired to write this article after the International Cricket Council (ICC) World Cup this past weekend. But admittedly, I was distracted by Google’s confetti when I tried to watch the …
Introduction to ETL Pipelines for Data Scientists
Author(s): Marcello Politi Originally published on Towards AI. Learn the basics of data engineering to improve your ML modelsPhoto by Mike Benna on Unsplash It is not news that developing Machine Learning algorithms requires data, often a lot of data. Collecting this …
Bridging the Implementation Gap of Artificial Intelligence in Healthcare
Author(s): Eera Bhatt Originally published on Towards AI. Each year, we spend so much time and money developing new machine learning models, but most of them never get used in a practical setting. Sadly, this issue is even worse in the healthcare …
Single Vs Multi-Task LLM Instruction Fine-Tuning
Author(s): Youssef Hosni Originally published on Towards AI. The comparative advantages and challenges of single-task versus multi-task fine-tuning of large language models (LLMs) are explored. The discussion begins with single-task fine-tuning, highlighting its benefits and drawbacks, including the issue of catastrophic forgetting. …
Gentle Introduction to LLMs
Author(s): Saif Ali Kheraj Originally published on Towards AI. Figure 1: https://finance.yahoo.com/news/explosive-growth-predicted-large-language-184300698.html The LLM market is expected to grow at a CAGR of 40.7%, reaching USD 6.5 billion by the end of 2024, and rising to USD 140.8 billion by 2033. Given …
Top Important LLMs Papers for the Week from 17/06 to 23/06
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Large Language Models Research Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the …
Top Important Computer Vision Papers for the Week from 17/06 to 23/06
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Computer Vision Research Every week, researchers from top research labs, companies, and universities publish exciting breakthroughs in various topics such as diffusion models, vision language models, image editing and generation, …
Counter Overfitting with L1 and L2 Regularization
Author(s): Eashan Mahajan Originally published on Towards AI. Photo by Arseny Togulev on Unsplash Overfitting. A modeling error many of us have encountered or will encounter while training a model. Simply put, overfitting is when the model learns about the details and …
Increasing Robustness and Equity in NLP for Various English Dialects
Author(s): Eera Bhatt Originally published on Towards AI. Natural language processing (NLP) is a popular subfield of machine learning that enables computers to interpret and use human language to achieve certain tasks. To do this, we have to train the computer on …
Want to Learn Quantization in The Large Language Model?
Author(s): Milan Tamang Originally published on Towards AI. Want to Learn Quantization in The Large Language Model? 1. Image by writer: Flow shows the need for quantization. (The happy face and angry face image is by Yan Krukau, https://www.pexels.com/) Before I explain …
How are LLMs creative?
Author(s): Sushil Khadka Originally published on Towards AI. If you’ve used any generative AI models such as GPT, Llama, etc., there’s a good chance you’ve encountered the term ‘temperature’. Photo by Khashayar Kouchpeydeh on Unsplash For starters, ‘temperature’ is a parameter that …
A Comprehensive Introduction to Instruction Fine-Tuning for LLMs
Author(s): Youssef Hosni Originally published on Towards AI. Instruction tuning is a process used to enhance large language models (LLMs) by refining their ability to follow specific instructions. OpenAI’s work on InstructGPT first introduced instruction fine-tuning. InstructGPT was trained to follow human …
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