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The Ultimate Roadmap to Becoming an LLM Engineer

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!

KDnuggets favicon KDnuggets β€’ 9 months ago β€’ 1 min read

10 Essential PySpark Commands for Big Data Processing

Check out these 10 ways to leverage efficient distributed dataset processing combining the strengths of Spark and Python libraries for data science.

KDnuggets favicon KDnuggets β€’ 9 months ago β€’ 1 min read

Future-Proof Your Machine Learning Career in 2025

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.

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RAG Isn’t Immune to LLM Hallucination

How to measure how much of your RAG’s output is correctContinue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

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.

KDnuggets favicon KDnuggets β€’ 9 months ago β€’ 1 min read

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...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 10 min read

The Concepts Data Professionals Should Know in 2025: Part 2

From AI Agent to Human-In-The-Loopβ€”Master 12 critical data concepts and turn them into simple projects to stay ahead in IT.Continue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

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. We’ll use Azure...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 19 min read

The Concepts Data Professionals Should Know in 2025: Part 1

From Data Lakehouses to Event-Driven Architectureβ€”Master 12 data concepts and turn them into simple projects to stay ahead in IT.Continue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

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 Skalski’s popular soccer tracking project, there’s been a notable shift towards using automated player tracking for sport hobbyists. Most of these approaches follow a familiar workflow: collect...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 10 min read

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...

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How to Pick Between Data Science, Data Analytics, Data Engineering, ML Engineering, and SW…

Make the right choice for YOUContinue reading on Towards Data Science Β»

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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 Β»

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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 Β»

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Satellite Image Classification with Deep Learningβ€Šβ€”β€ŠComplete Project

A Comprehensive Guide Using PyTorch and CNNsContinue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

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 Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

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,...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 21 min read

Where to Start when Data is Limited: A Guide

Overcome small data constraints & ambitious performance requirements – 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...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 21 min read

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...

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A Practical Exploration of Soraβ€Šβ€”β€ŠIntuitively and Exhaustively Explained

A new cutting edge video generation tool, and the theory behind itContinue reading on Towards Data Science Β»

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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.

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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 Β»

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Preparing PDFs for RAGs

I created a graph storage from dozens of annual reports (with tables)Continue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

AI is Getting Smarter, But It Still Can’t Do My Data Science Job.

A product data scientist breaks down why AI won’t replace us anytime soon.

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Influential Time-Series Forecasting Papers of 2023–2024: Part 1

Exploring the latest advancements in time seriesContinue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

What Did I Learn from Building LLM Applications in 2024?β€Šβ€”β€ŠPart 2

What Did I Learn from Building LLM Applications in 2024?β€”Part2An engineer’s journey to building LLM-powered applicationsIllustration of building AI application (image by authorβ€”generated 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. Let’s pick it up from thereβ€”if you are fairly...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 13 min read

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.

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Learnings from a Machine Learning Engineerβ€Šβ€”β€ŠPart 4: The Model

Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science Β»

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Learnings from a Machine Learning Engineerβ€Šβ€”β€ŠPart 3: The Evaluation

Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

Learnings from a Machine Learning Engineerβ€Šβ€”β€ŠPart 2: The Data Sets

Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

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 Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

The Data Analyst Every CEO Wants

Data Analyst is probably the most underrated job in the data industryContinue reading on Towards Data Science Β»

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 1 min read

MAS Is All You Need: Supercharge Your Retrieval-Augmented Generation (RAG) with a Multi-Agent…

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...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 18 min read

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...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 19 min read

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 isn’t capable of correctly answering the questions you have.But when an experiment works out, it...

Towards Data Science favicon Towards Data Science β€’ 9 months ago β€’ 10 min read