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#General #Development #Mobile Development #Cloud & DevOps #Cybersecurity & Privacy #AI & Data Science #Hardware & Gadgets #Design & UXA Multimodal AI Assistant: Combining Local and Cloud Models
Dalle-3’s interpretation of “a quirky robot wearing a tool belt and puzzling over question”. Image generated by theauthor.Use LangGraph, mlx and Florence2 to build an agent that answers complex image questions, with the option to run everything locally.In this article we’ll use LangGraph in conjunction with several specialized models to build a rudimentary agent that can answer complex questions about an image,...
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Going Beyond Bias-Variance Tradeoff Into Double Descent Phenomenon
It’s not how many times you get knocked down that count, it’s how many times you get back up.Continue reading on Towards Data Science »
IT Strategies: Built to Last
Why Reevaluating Our Core Assumptions About Data and Integration Creates Significant ValueContinue reading on Towards Data Science »
Building Deterministic GenAI Chatbots In Regulated Industries
How to Build Reliable and Contextual AI Chatbots for Finance, Healthcare and Other IndustriesContinue reading on Towards Data Science »
How I Would Learn Python in 2025 (If I Could Start Over)
I’ve been programming with Python for over 6 years now. But if I could start over, here’s how I’d go about learning Python in 2025.
Understanding the Evolution of ChatGPT: Part 2 — GPT-2 and GPT-3
Understanding the Evolution of ChatGPT: Part 2—GPT-2 andGPT-3Scaling from 117M to 175B: Insights into GPT-2 andGPT-3.(Image from Unsplash)This is the second article of our GPT series, where we will dive into the development of GPT-2 and GPT-3, with model size increased from 117M to a staggering 175B.In case you are interested in the first article which covers GPT-1 as well as the techniques inspired it, check this...
Complete Guide to Cross-Validation
This guide will explore the ins and outs of cross-validation, examine its different methods, and discuss why it matters in today's data science and machine learning processes.
AI Agents Simplified: How AI Agents Answer Questions Using Domain Knowledge
Demystify how enterprise AI agents are tailored to answer client questions using domain knowledge and confine answers to domain knowledgeContinue reading on Towards Data Science »
A Practical Guide to the Claude API
The API for
Using Constraint Programming to Solve Math Theorems
Case study: the quasigroups existence problemTLDRSome mathematical theorems can be solved by combinatorial exploration. In this article, we focus on the problem of the existence of some quasigroups. We will demonstrate the existence or non existence of some quasigroups using NuCS. NuCs is a fast constraint solver written 100% in Python that I am currently developing as a side project. It is released under the MIT...
What is MicroPython? Do I Need to Know it as a Data Scientist?
In this year’s edition of the Stack Overflow survey, MicroPython is with 1.6% in the Most Popular Technologies—but why?Continue reading on Towards Data Science »
Your Classifier Is Broken, But It Is Still Useful
When you run a binary classifier over a population you get an estimate of the proportion of true positives in that population. This is known as the prevalence.Photo by Rod Long onUnsplashBut that estimate is biased, because no classifier is perfect. For example, if your classifier tells you that you have 20% of positive cases, but its precision is known to be only 50%, you would expect the true prevalence to be 0.2 ...
What Would a Stoic Do? — An AI-Based Decision-Making Model
Using AI to build Marcus Aurelius’ reincarnationContinue reading on Towards Data Science »
LightGBM: The Fastest Option of Gradient Boosting
Learn how to implement a fast and effective Gradient Boosting model using PythonContinue reading on Towards Data Science »
Machine Learning + openAI: solving a text classification problem
How I migrated an old solution to a more elegant, robust and scalable solution using text classification from openAIContinue reading on Towards Data Science »
Exploring New Hyperparameter Dimensions with Laplace Approximated Bayesian Optimization
Is it better than gridsearch?Image by author fromcanvaWhen I notice my model is overfitting, I often think, “It is time to regularize”. But how do I decide which regularization method to use (L1, L2) and what parameters to choose? Typically, I perform hyperparameter optimization by means of a grid search to select the settings. However, what happens if the independent variables have different scales or varying levels...
Building Visual Agents that can Navigate the Web Autonomously
A step-by-step guide to creating visual agents that can navigate the web autonomouslyContinue reading on Towards Data Science »
A Visual Understanding of Neural Networks
The math behind neural networks visually explainedContinue reading on Towards Data Science »
3 Powerful Examples of the Python Re Library
Explore the power of regex and save time in data analysisContinue reading on Towards Data Science »
Solving A Rubik's Cube with Supervised Learning — Intuitively and Exhaustively Explained
A Popular Toy in a Brave New WorldContinue reading on Towards Data Science »
How to Monitor Docker Containers
This guide highlights the importance of container monitoring, key metrics to track, and tools ranging from Docker's built-in commands to comprehensive systems like Prometheus and Grafana.
Model Calibration, Explained: A Visual Guide with Code Examples for Beginners
MODEL EVALUATION & OPTIMIZATIONWhen all models have similar accuracy, nowwhat?You’ve trained several classification models, and they all seem to be performing well with high accuracy scores. Congratulations!But hold on—is one model truly better than the others? Accuracy alone doesn’t tell the whole story. What if one model consistently overestimates its confidence, while another underestimates it? This is where...
Sustainable Business Strategy with Data Analytics
Use data analytics to help companies design and implement strategic sustainability roadmaps to reduce their environmental footprint.Sustainable Business Strategy with Analytics—(Image by SamirSaci)Consensus means that everyone agrees to say collectively what no one believes individually.This quote captures a critical issue many companies face during their strategic green transformation: aligning diverse objectives...
7 Advanced AI Projects for Beginners
Build your own state-of-the-art AI applications with simple steps and beginner-friendly methodologies.
Linearizing Llama
Speeding up Llama: A hybrid approach to attention mechanismsSource: Image by Author (Generated using Gemini 1.5Flash)In this article, we will see how to replace softmax self-attention in Llama-3.2-1B with hybrid attention combining softmax sliding window and linear attention. This implementation will help us better understand the growing interest in linear attention research, while also examining its limitations and...
Mastering Transparent Images: Adding a Background Layer
How to Process Images with an Alpha Channel using OpenCV +PythonAdding a Colored Background to an Image with an AlphaChannelRecently, I needed to add a white background to a couple of images with a transparent background. Naturally, I used Python with OpenCV to automate the process, I wasn’t going to open an image editor for each of theseimages.Adding a background colorsoundseasyenough,right?Well, on my first attempt...
The Best Way to Prepare for Data Science and Machine Learning Interviews
Never get stumped againContinue reading on Towards Data Science »
Sentiment Analysis with Transformers: A Complete Deep Learning Project — PT. I
Master Fine-Tuning Transformers, Comparing Deep Learning Architectures, and Deploying Sentiment Analysis ModelsContinue reading on Towards Data Science »
What to Do If the Logit Decision Boundary Fails?
Feature engineering for classification models using Bayesian Machine LearningContinue reading on Towards Data Science »
How to Run Jupyter Notebooks and Generate HTML Reports with Python Scripts
A step-by-step guide to automating Jupyter Notebook execution and report generation using PythonContinue reading on Towards Data Science »
Building Autonomous Multi-Tool Agents with Gemini 2.0 and LangGraph
A practical tutorial with full code examples for building and running multi-tool agentsContinue reading on Towards Data Science »
RAG Hallucination Detection Techniques
Large language models (LLMs) are useful for many applications, including question answering, translation, summarization, and much more, with recent advancements in the area having increased their potential.
How Large Language Models (LLMs) Learn: Playing Games
LLMs are just professional Mad Libs PlayersContinue reading on Towards Data Science »
How I Would Learn Data Science in 2025 (If I Could Start Over)
Five years ago, I was a data science beginner learning the ropes. If I could start anew in 2025, here's what I would do.
LLM Evaluation, Parallel Computing, Demand Forecasting, and Other Hands-On Data Science Approaches
Feeling inspired to write your first TDS post? We’re always open to contributions from newauthors.As we all settle into the sometimes hectic rhythm of a new year, we hope you’ve been enjoying the excitement of kicking off projects, learning about new topics, and exploring your next career moves. We’re definitely seeing a flurry of activity among our authors—both longstanding contributors and recent additions—and are...