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#General #Development #Mobile Development #Cloud & DevOps #Cybersecurity & Privacy #AI & Data Science #Hardware & Gadgets #Design & UXNine Pico PIO Wats with Rust (Part 1)
Raspberry Pi programmable IO pitfalls illustrated with a musicalexamplePico PIO Surprises—Source: https://openai.com/dall-e-2/. All other figures from theauthor.Also available: A MicroPython version of thisarticleIn JavaScript and other languages, we call a surprising or inconsistent behavior a “Wat!” [that is, a “What!?”]. For example, in JavaScript, an empty array plus an empty array produces an empty string, [] + []...
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Contextual Bandit Simulation in Marketing
When A/B Tests Are Not The RightChoiceBandit Algorithm Or A/BTest?Imagine working as a Data Scientist for an adtech company and you are serving ads on behalf of a client. If that client comes to you and says that they have 2 variants in mind (i.e. changes to creative / message / offer ) for their upcoming campaign and they want to figure out “which ad is best”, what do you do? Run an A/B test where you randomly split...
Time Series Forecasting with MFLES
The newest method in StatsForecastContinue reading on Towards Data Science »
How to Summarize Scientific Papers Using the BART Model with Hugging Face Transformers
Learn how to perform paper summarization with BART.
An Introduction to Logarithms in Machine Learning with Python
Logarithms are a cornerstone of mathematics, statistics, and data science, and even show up in all sorts of places in machine learning.
How to Run Parallel Time Series Analysis with Dask
In this article, we show you how to run parallel time series analysis with Dask, through a practical Python-based tutorial.
Optimizing Memory Usage in PyTorch Models
Even though more than 40% of businesses say they’re pleased with AI, many are unhappy with out-of-the-box solutions, resulting in a need for local AI solutions and their subsequent tweaking with PyTorch.
Great Books for AI Engineering
10 books with valuable insights about AI science and engineeringGreat books for AI Engineering—Plus ‘Brave New Words’ (Image is Author’s ownwork)A few years ago I recommended 21 books in Great Books for Data Science and Great Books for Data Science 2. Since then a lot has changed. While data scientist and machine learning engineer continue to be necessary functions in large companies, the specific role of AI engineer...
AI Ethics for the Everyday User — Why Should You Care?
A beginner’s guide to understanding the importance of ethics in artificial intelligenceContinue reading on Towards Data Science »
NLP Illustrated, Part 3: Word2Vec
An exhaustive and illustrated guide to Word2Vec with code!Continue reading on Towards Data Science »
The Challenges and Realities of Being a Data Scientist
Some harsh truths behind the field of data scienceContinue reading on Towards Data Science »
Machine Learning Incidents in AdTech
Source: https://unsplash.com/photos/a-couple-of-signs-that-are-on-a-fence-xXbQIrWH2_AChallenges with deep learning in productionOne of the biggest challenges I encountered in my career as a data scientist was migrating the core algorithms in a mobile AdTech platform from classic machine learning models to deep learning. I worked on a Demand Side Platform (DSP) for user acquisition, where the role of the ML models is to...
Coding with Qwen 2.5: An Overview
Code smarter, not harder with Qwen 2.5.
Prompting Vision Language Models
Exploring techniques to promptVLMsVision Language Models (VLMs) represent a significant advancement in processing and understanding multimodal data by combining text and visualinputs.High Level Overview of VLMs. The picture of the cute dog is from Josh Frenette on Unsplash. This image is inspired by the representation of VLMs provided in this blog from HuggingFace (https://huggingface.co/blog/vlms) (Overall Image By...
From Spell Check to AI
Why using tools is notcheatingCreated by Author usingDall-EI have been working in the field of AI since 1983. While I don’t claim the title of expert (I’ll leave claiming that title to those who write articles about doomsday, and Skynet Terminators coming to steal our jobs), I frequently get asked to speak on the subject of AI. I always start by asking a simple question: “How many of you use AI in your everyday lives?”...
Data Wrangling in Rust with Polars
Looking for efficient data wrangling in Rust? Polars offers fast, memory-safe tools for tasks like filtering, joining, and aggregating data.
The SCORES Framework: A Data Scientist’s Guide to Winning Target Variables
The missing manual for defining target variables that matter—bridge the gap between business goals and impactful MLmodelsPhoto by Jeffrey F Lin onUnsplashPerfect accuracy on the wrong target variable is like acing the wrongexam- technically impressive, but missing the point entirely.Target variables or dependent variables are critical for the success of your machine learningmodel.When starting to work on a new model,...
Exploring DeepSeek’s R1 Training Process
Open-Source Intelligence on Par with Proprietary ModelsContinue reading on Towards Data Science »
Analyze Tornado Data with Python and GeoPandas
Insights from NOAA’s public domain databaseContinue reading on Towards Data Science »
Basics of Probability Notations
Union, Intersection, Independence, Disjoint, Complement: Advanced Probability for Data Science Series (1)Continue reading on Towards Data Science »
How GenAI Tools Have Changed My Work as a Data Scientist
An overview of the 4 use cases and 6 GenAI tools I useContinue reading on Towards Data Science »
How to do Date calculations in DAX
Moving back and forth in time is a common task for Time Intelligence in DAX. Let’s take a deeper look on how DATEADD() works.Continue reading on Towards Data Science »
The Role of AI in Shaping the Future of Work
Rather than fearing AI, we should see it as a tool that complements human skills, helping professionals focus on high-value work and enhancing job roles.
Don’t Manage Your Python Environments, Just Use Docker Containers
Python environment management can sometimes give you that awful feeling in the pit of your stomach. So don't do it: just use Docker containers.
Who is Right? The Dean or the Students?
A cautionary tale on two perspectives on averagingContinue reading on Towards Data Science »
Chain-of-Agents Meets Mechanism Design
Aligning Incentives for Multi-Agent LLM Collaboration on Long-Context TasksContinue reading on Towards Data Science »
How to Evaluate LLMs
Evaluation methodologies, metrics, and best practices for different language tasks, explained.
Battle of the Ducks
DuckDB vs Fireducks: the ultimate throwdownContinue reading on Towards Data Science »
The Three Phases of Learning Machine Learning
Part One: The beginner phaseContinue reading on Towards Data Science »
Nine Pico PIO Wats with MicroPython (Part 2)
Raspberry Pi programmable IO pitfalls illustrated with a musicalexamplePico PIO Surprises, Part 2—Source: https://openai.com/dall-e-2/. All other figures from theauthor.This is Part 2 of an exploration into the unexpected quirks of programming the Raspberry Pi Pico PIO with MicroPython. If you missed Part 1, we uncovered four Wats that challenge assumptions about register count, instruction slots, the behavior of...
One Machine Learning Model, To-Go Please
How to use ONNX to make any machine learning model portableContinue reading on Towards Data Science »
Creating Powerful Ensemble Models with PyCaret
Machine learning is changing how we solve problems.
Building a Regression Model: Delivery Duration Prediction
Building a Regression Model to Predict Delivery Durations: A Practical GuideE2E walkthrough for approaching a regression modelingtaskIn this article, we’re going to walk through the process of building a regression model—from dataset cleaning & preparation, to model training & evaluation. The specific regression task we will model for is predicting the expected delivery time for a food delivery...
Beyond Causal Language Modeling
A deep dive into “Not All Tokens Are What You Need for Pretraining”IntroductionA few days ago, I had the chance to present at a local reading group that focused on some of the most exciting and insightful papers from NeurIPS 2024. As a presenter, I selected a paper titled “Not All Tokens Are What You Need for Pretraining”. It addresses a super simple but reasonable question: do we really need to apply the next-token...
How to Implement Guardrails for Your AI Agents with CrewAI
LLM Agents are non-deterministic by nature: implement proper guardrails for your AI Application.Continue reading on Towards Data Science »