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10 Data Science Myths Debunked [Infographic]
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.
Published on: January 20, 2025 | Source:
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Five Key Lessons for Google Earth Engine Beginners
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...
Published on: January 20, 2025 | Source:The Concepts Data Professionals Should Know in 2025: Part 2
From AI Agent to Human-In-The-LoopโMaster 12 critical data concepts and turn them into simple projects to stay ahead in IT.Continue reading on Towards Data Science ยป
Published on: January 20, 2025 | Source:Designing, Building & Deploying an AI Chat App from Scratch (Part 2)
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. Weโll use Azure...
Published on: January 20, 2025 | Source:The Concepts Data Professionals Should Know in 2025: Part 1
From Data Lakehouses to Event-Driven ArchitectureโMaster 12 data concepts and turn them into simple projects to stay ahead in IT.Continue reading on Towards Data Science ยป
Published on: January 19, 2025 | Source:Zero-Shot Player Tracking in Tennis with Kalman Filtering
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 Skalskiโs popular soccer tracking project, thereโs been a notable shift towards using automated player tracking for sport hobbyists. Most of these approaches follow a familiar workflow: collect...
Published on: January 19, 2025 | Source:How to Log Your Data with MLflow
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...
Published on: January 19, 2025 | Source:How to Pick Between Data Science, Data Analytics, Data Engineering, ML Engineering, and SWโฆ
Make the right choice for YOUContinue reading on Towards Data Science ยป
Published on: January 19, 2025 | Source:Showcasing Soaring Wildfire Counts With Streamlit and Python: A Powerful Approach
Analyzing historical wildfire trends in Canada with public dataContinue reading on Towards Data Science ยป
Published on: January 18, 2025 | Source:How to Use Pre-Trained Language Models for Regression
Why and how to convert mT5 into a regression metric for numerical predictionContinue reading on Towards Data Science ยป
Published on: January 18, 2025 | Source:Satellite Image Classification with Deep LearningโโโComplete Project
A Comprehensive Guide Using PyTorch and CNNsContinue reading on Towards Data Science ยป
Published on: January 17, 2025 | Source:My Experience Switching From Power BI to Looker (as a Senior Data Analyst)
What you need to know before you switch from Power BI to Looker.Continue reading on Towards Data Science ยป
Published on: January 17, 2025 | Source:Where to Start When Data is Limited
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,...
Published on: January 17, 2025 | Source:Where to Start when Data is Limited: A Guide
Overcome small data constraints & ambitious performance requirements โ 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...
Published on: January 17, 2025 | Source:Learning from Machine Learning | Sebastian Raschka: Mastering ML and Pushing AI Forward Responsibly
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...
Published on: January 17, 2025 | Source:A Practical Exploration of SoraโโโIntuitively and Exhaustively Explained
A new cutting edge video generation tool, and the theory behind itContinue reading on Towards Data Science ยป
Published on: January 17, 2025 | Source:10 Python One-Liners That Will Change Your Coding Game
A not-to-be-missed list of elegant Python solutions to perform common programming and processing tasks in a single line of code.
Published on: January 17, 2025 | Source:LLM for Data Visualization: How AI Shapes the Future of Analytics
From Raw Data to Stunning Visuals: LLMs in ActionContinue reading on Towards Data Science ยป
Published on: January 17, 2025 | Source:Preparing PDFs for RAGs
I created a graph storage from dozens of annual reports (with tables)Continue reading on Towards Data Science ยป
Published on: January 17, 2025 | Source:AI is Getting Smarter, But It Still Canโt Do My Data Science Job.
A product data scientist breaks down why AI wonโt replace us anytime soon.
Published on: January 17, 2025 | Source:Influential Time-Series Forecasting Papers of 2023โ2024: Part 1
Exploring the latest advancements in time seriesContinue reading on Towards Data Science ยป
Published on: January 17, 2025 | Source:What Did I Learn from Building LLM Applications in 2024?โโโPart 2
What Did I Learn from Building LLM Applications in 2024?โPart2An engineerโs journey to building LLM-powered applicationsIllustration of building AI application (image by authorโgenerated 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. Letโs pick it up from thereโif you are fairly...
Published on: January 17, 2025 | Source:The Roadmap for Mastering Machine Learning in 2025
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.
Published on: January 17, 2025 | Source:Learnings from a Machine Learning EngineerโโโPart 4: The Model
Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science ยป
Published on: January 17, 2025 | Source:Learnings from a Machine Learning EngineerโโโPart 3: The Evaluation
Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science ยป
Published on: January 16, 2025 | Source:Learnings from a Machine Learning EngineerโโโPart 2: The Data Sets
Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science ยป
Published on: January 16, 2025 | Source:Top 3 Questions to Ask in Near Real-Time Data Solutions
Questions that guide architectural decisions to balance functional requirements with non-functional ones, like latency and scalabilityContinue reading on Towards Data Science ยป
Published on: January 16, 2025 | Source:The Data Analyst Every CEO Wants
Data Analyst is probably the most underrated job in the data industryContinue reading on Towards Data Science ยป
Published on: January 16, 2025 | Source:MAS Is All You Need: Supercharge Your Retrieval-Augmented Generation (RAG) with a Multi-Agentโฆ
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...
Published on: January 16, 2025 | Source:The Large Language Model Course
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...
Published on: January 16, 2025 | Source:How We Optimized Premium Listings on Our Nursing Job Board
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 isnโt capable of correctly answering the questions you have.But when an experiment works out, it...
Published on: January 16, 2025 | Source:Building a Custom Model Pipeline in PyCaret: From Data Prep to Production
Building a custom model pipeline in
Published on: January 16, 2025 | Source:An Introduction to Ray: The Swiss Army Knife of Distributed Computing
Need a simple way to scale Python applications? Ray makes distributed computing easy for tasks like machine learning and data processing.
Published on: January 16, 2025 | Source:Charts, Dashboards, Maps, and More: Data Visualization in the Spotlight
Feeling inspired to write your first TDS post? Weโre always open to contributions from newauthors.Buzzwords and trends come and go, but the core task of telling compelling stories with data remains one of the main pillars in data scientistsโ daily workflow. For practitioners whoโd like to up their visualization game, this week weโre highlighting some of our best recent articles on creating powerful, effective, and...
Published on: January 16, 2025 | Source:Why Data Scientists Canโt Afford Too Many Dimensions and What They Can Do About It
An in-depth article about dimensionality reduction and its most popular methodsContinue reading on Towards Data Science ยป
Published on: January 16, 2025 | Source: