Retrieval augmented generation (RAG) has become a vital technique in contemporary AI systems, allowing large language models (LLMs) to integrate external data in real time. This approach empowers models to ground their responses in precise information extracted from relevant sources, leading to better performance in tasks such as question-answering, summarization, and content generation. By augmenting […]
Machine learning is now the cornerstone of recent technological progress, which is especially true for the current generative AI stampede. Many use tools such as ChatGPT, Perplexity and Midjourney to help in their day-to-day work, strong evidence that machine learning will continue to shape how we approach work for a long time to come. Closing […]
Artificial intelligence (AI) research, particularly in the machine learning (ML) domain, continues to increase the amount of attention it receives worldwide. To give you an idea of the scientific hype around AI and ML, the number of works uploaded to the open-access pre-print archive ArXiv has nearly doubled since late 2023, with over 30K AI-related […]
Machine learning (ML) models are built upon data. They are like the ready-to-use artifacts resulting from making sense of a dataset to uncover patterns, make predictions, or automate decisions. Whilst visualizing data is undoubtedly important across many data science processes like exploratory analysis and feature engineering, the idea of visualizing an ML model is not […]
The adoption of machine learning (ML) continues at a rapid pace, as it has proven itself a powerful tool for solving many problems. A good way to learn ML is by working on projects, especially those that are able to give you real, valuable experience. In this article, we will discuss 7 simple machine learning […]
Podcasts are a fun and easy way to learn about machine learning. Machine learning is a fast-changing field. New ideas and tools come out all the time. Podcasts help you stay updated on these changes. They often feature interviews with experts and researchers. You can hear about their work and get insights into the latest […]
In real life, the machine learning model is not a standalone object that only produces a prediction. It is part of an extended system that can only provide values if we manage it together. We need the machine learning (ML) pipeline to operate the model and deliver value. Building an ML pipeline would require us […]
Are you a machine learning enthusiast looking to level up your skills? If so, contributing to open-source machine learning projects is one of the best ways to improve your coding skills. When you work on open-source ML tools, you’ll learn more about how ML frameworks work internally. You’ll also get to improve your coding […]
Computer vision is a branch of Artificial Intelligence (AI) that studies how machines can interpret and understand visual information, such as images and videos. Most computer vision models today are based on deep learning architectures like Convolutional Neural Networks (CNNs), which excel at tasks such as image classification, object detection, and segmentation. However, the necessary […]
As data scientists with Python programming skills, we use Scikit-Learn a lot. It’s a machine learning package usually taught to new users initially and can be used right through to production. However, much of what is being taught is basic implementation, and Scikit-Learn contains many secrets to improve our data workflow. This article will discuss […]
