Implementing the classic Pong game in Python using OOP and Turtle
The post Coding the Pong Game from Scratch in Python appeared first on Towards Data Science.
The Gap Between Junior and Senior Data Scientists Isn’t Code
Why my obsession with complex algorithms was actually holding my career back.
The post The Gap Between Junior and Senior Data Scientists Isn’t Code appeared first on Towards Data Science.
A Generalizable MARL-LP Approach for Scheduling in Logistics
Part 1. Hybrid Solution for Dynamic Vehicle Routing — Context and Architecture
The post A Generalizable MARL-LP Approach for Scheduling in Logistics appeared first on Towards Data Science.
Have you ever wondered what happens when you apply a filter in a DAX expression? Well, Today I will take you on a deep dive into this fascinating topic, with examples to help you learn something new and surprising.
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How to Define the Modeling Scope of an Internal Credit Risk Model
Dataset construction for Internal Ratings-Based (IRB) Probability of Default (PD) models
The post How to Define the Modeling Scope of an Internal Credit Risk Model appeared first on Towards Data Science.
AI in Multiple GPUs: Gradient Accumulation & Data Parallelism
Learn and implement gradient accum and data parallelism from scratch in PyTorch
The post AI in Multiple GPUs: Gradient Accumulation & Data Parallelism appeared first on Towards Data Science.
An End-to-End Guide to Beautifying Your Open-Source Repo with Agentic AI
The guide to automated improvement of scientific and industrial repositories using open-source AI agents
The post An End-to-End Guide to Beautifying Your Open-Source Repo with Agentic AI appeared first on Towards Data Science.
A pragmatic journey using website analytics as a real-world example
The post From Monolith to Contract-Driven Data Mesh appeared first on Towards Data Science.
Understanding the Chi-Square Test Beyond the Formula
How categorical data becomes statistical evidence.
The post Understanding the Chi-Square Test Beyond the Formula appeared first on Towards Data Science.
A deep dive into the hardware infrastructure that enables multi-GPU communication for AI workloads
The post AI in Multiple GPUs: How GPUs Communicate appeared first on Towards Data Science.
Why Every Analytics Engineer Needs to Understand Data Architecture
Get the data architecture right, and everything else becomes easier.
I know it sounds simple, but in reality, little nuances in designing your data architecture may have costly implications. This article provides a crash course on the architectures that shape your daily decisions - from relational d...
A beginner’s guide to Tmux: a multitasking superpower for your terminal
One of the new things I’ve come across recently, while researching command-line-based coding assistants, is the mention and use of a tool I hadn’t heard of before. That tool is called Tmux, which stands for Terminal Multiplexer. In the simplest possible terms, Tmux allows you to split up a single t...
AI in Multiple GPUs: Point-to-Point and Collective Operations
Learn PyTorch distributed operations for multi GPU AI workloads
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How to Leverage Explainable AI for Better Business Decisions
Moving beyond the black box to turn complex model outputs into actionable organizational strategies.
The post How to Leverage Explainable AI for Better Business Decisions appeared first on Towards Data Science.
AI in Multiple GPUs: Understanding the Host and Device Paradigm
Learn how CPU and GPUs interact in the host-device paradigm
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How baseline strength, churn, and subjectivity determine complexity
The post Not All RecSys Problems Are Created Equal appeared first on Towards Data Science.
How to Model The Expected Value of Marketing Campaigns
The approach that takes companies to the next level of data maturity
The post How to Model The Expected Value of Marketing Campaigns appeared first on Towards Data Science.
Learn how to get more out of Claude code by giving it access to more information.
The post How to Personalize Claude Code appeared first on Towards Data Science.
The Machine Learning Lessons I’ve Learned Last Month
Delayed January: deadlines, downtimes, and flow times
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