Get ahead of the curve with the latest insights, trends, and analysis in the tech world.
Unsure what to learn, where to start, and which order to follow to master LLM engineering concepts and skills? This comprehensive roadmap with clear milestones and stages is here to help!
Check out these 10 ways to leverage efficient distributed dataset processing combining the strengths of Spark and Python libraries for data science.
Machine learning continues to provide benefits of all sorts that have become integrated within society, meaning that a career in machine learning will only become more important with time.
How to measure how much of your RAGβs output is correctContinue reading on Towards Data Science Β»
Our latest infographic breaks down 10 of the most common and enduring myths about data science, offering clarity on the misconceptions that often surround this rapidly evolving field.
Hands-On Insights from a Python APIuserLand cover map for the Paute water bassin in Ecuador for the year 2020. Image created using Google Earth Engine Python API and Geemap. Data source: Friedl, M., Sulla-Menashe, D. (2022); Lehner, B., Grill G. (2013) and Lehner, B., Verdin, K., Jarvis, A.(2008).IntroductionAs a climate scientist, Google Earth Engine (GEE) is a powerful tool in my toolkit. No more downloading heavy...
From AI Agent to Human-In-The-LoopβMaster 12 critical data concepts and turn them into simple projects to stay ahead in IT.Continue reading on Towards Data Science Β»
Cloud Deployment andScalingPhoto by Alex wong onUnsplash1. IntroductionIn the previous post, we built an AI-powered chat application on our local computer using microservices. Our stack included FastAPI, Docker, Postgres, Nginx and llama.cpp. The goal of this post is to learn more about the fundamentals of cloud deployment and scaling by deploying our app to Azure, making it available to real users. Weβll use Azure...
From Data Lakehouses to Event-Driven ArchitectureβMaster 12 data concepts and turn them into simple projects to stay ahead in IT.Continue reading on Towards Data Science Β»
Automated tennis tracking without labels: GroundingDINO, Kalman filtering, and court homographyhttps://medium.com/media/6f735abc63f905de122bb8a0679f97fd/hrefWith the recent surge in sports tracking projects, many inspired by Skalskiβs popular soccer tracking project, thereβs been a notable shift towards using automated player tracking for sport hobbyists. Most of these approaches follow a familiar workflow: collect...
MLflow, MLOps, DataScienceMastering data logging in MLOps for your AIworkflowPhoto by Chris Liverani onUnsplashPrefaceData is one of the most critical components of the machine learning process. In fact, the quality of the data used in training a model often determines the success or failure of the entire project. While algorithms and models are important, they are powerless without data that is accurate, clean, and...
Make the right choice for YOUContinue reading on Towards Data Science Β»
Analyzing historical wildfire trends in Canada with public dataContinue reading on Towards Data Science Β»
Why and how to convert mT5 into a regression metric for numerical predictionContinue reading on Towards Data Science Β»
A Comprehensive Guide Using PyTorch and CNNsContinue reading on Towards Data Science Β»
What you need to know before you switch from Power BI to Looker.Continue reading on Towards Data Science Β»
A launch pad for projects with smalldatasetsPhoto by Google DeepMind: https://www.pexels.com/photo/an-artist-s-illustration-of-artificial-intelligence-ai-this-image-depicts-how-ai-can-help-humans-to-understand-the-complexity-of-biology-it-was-created-by-artist-khyati-trehan-as-part-17484975/Machine Learning (ML) has driven remarkable breakthroughs in computer vision, natural language processing, and speech recognition,...
Overcome small data constraints & ambitious performance requirements β leveraging modern ML to surpass conventional methods.Photo by Google DeepMind: https://www.pexels.com/photo/an-artist-s-illustration-of-artificial-intelligence-ai-this-image-depicts-how-ai-can-help-humans-to-understand-the-complexity-of-biology-it-was-created-by-artist-khyati-trehan-as-part-17484975/Machine Learning (ML) has driven remarkable...
Sebastian Raschka has helped demystify deep learning for thousands through his books, tutorials and teachingsSebastian Raschka has helped shape how thousands of data scientists and machine learning engineers learn their craft. As a passionate coder and proponent of open-source software, a contributor to scikit-learn and the creator of the mlxtend library, his code runs in production systems worldwide. But his greatest...
A new cutting edge video generation tool, and the theory behind itContinue reading on Towards Data Science Β»
A not-to-be-missed list of elegant Python solutions to perform common programming and processing tasks in a single line of code.
From Raw Data to Stunning Visuals: LLMs in ActionContinue reading on Towards Data Science Β»
I created a graph storage from dozens of annual reports (with tables)Continue reading on Towards Data Science Β»
A product data scientist breaks down why AI wonβt replace us anytime soon.
Exploring the latest advancements in time seriesContinue reading on Towards Data Science Β»
What Did I Learn from Building LLM Applications in 2024?βPart2An engineerβs journey to building LLM-powered applicationsIllustration of building AI application (image by authorβgenerated usingDALLE-3)In part 1 of this series, we discussed use case selection, building a team and the importance of creating a prototype early into your LLM-based product development journey. Letβs pick it up from thereβif you are fairly...
Machine learning (ML) is now a part of our daily lives, from the voice assistants on our mobiles to advanced robots performing tasks similar to humans.
Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science Β»
Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science Β»
Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science Β»
Questions that guide architectural decisions to balance functional requirements with non-functional ones, like latency and scalabilityContinue reading on Towards Data Science Β»
Data Analyst is probably the most underrated job in the data industryContinue reading on Towards Data Science Β»
Photo by julien Tromeur onUnsplashMAS Is All You Need: Supercharge Your Retrieval-Augmented Generation (RAG) with a Multi-Agent SystemHow to build a Multi-Agent RAG with AG2 andChromaDBRetrieval-Augmented Generation (RAG) systems have improved rapidly in recent years. Ideally, we can distinguish their evolution into three phases: in the pre-LLM era, information retrieval systems primarily relied on traditional search...
How to become an LLM Scientist and Engineer fromscratchImage byauthorThe Large Language Model (LLM) course is a collection of topics and educational resources for people to get into LLMs. It features two main roadmaps: The LLM Scientist focuses on building the best possible LLMs using the latest techniques. The LLM Engineer focuses on creating LLM-based applications and deploying them.For an interactive version of this...
Geo-randomization & how you might approach a problem with no historical dataOne of my favorite things to talk to other data scientists or product leaders about is experiments.A lot of experiments fail. Sometimes an idea works at one company and fails foranother.Sometimes you run an experiment and find out later the data isnβt capable of correctly answering the questions you have.But when an experiment works out, it...