📌 Optimizing Deep Learning Models with SAM
🗂 Category: DEEP LEARNING
🕒 Date: 2026-02-24 | ⏱️ Read time: 16 min read
A deep dive into the Sharpness-Aware-Minimization (SAM) algorithm and how it improves the generalizability of…
#DataScience #AI #Python
🗂 Category: DEEP LEARNING
🕒 Date: 2026-02-24 | ⏱️ Read time: 16 min read
A deep dive into the Sharpness-Aware-Minimization (SAM) algorithm and how it improves the generalizability of…
#DataScience #AI #Python
❤1
📌 AI Bots Formed a Cartel. No One Told Them To.
🗂 Category: AGENTIC AI
🕒 Date: 2026-02-24 | ⏱️ Read time: 11 min read
Inside the research that shows algorithmic price-fixing isn’t a bug in the code. It’s a…
#DataScience #AI #Python
🗂 Category: AGENTIC AI
🕒 Date: 2026-02-24 | ⏱️ Read time: 11 min read
Inside the research that shows algorithmic price-fixing isn’t a bug in the code. It’s a…
#DataScience #AI #Python
📌 Optimizing Token Generation in PyTorch Decoder Models
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-24 | ⏱️ Read time: 17 min read
Hiding host-device synchronization via CUDA stream interleaving
#DataScience #AI #Python
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-24 | ⏱️ Read time: 17 min read
Hiding host-device synchronization via CUDA stream interleaving
#DataScience #AI #Python
❤1
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📌 Decisioning at the Edge: Policy Matching at Scale
🗂 Category: DATA SCIENCE
🕒 Date: 2026-02-24 | ⏱️ Read time: 13 min read
Policy-to-Agency Optimization with PuLP
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2026-02-24 | ⏱️ Read time: 13 min read
Policy-to-Agency Optimization with PuLP
#DataScience #AI #Python
❤2
📌 Aliasing in Audio, Easily Explained: From Wagon Wheels to Waveforms
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-02-25 | ⏱️ Read time: 21 min read
Understanding the foundational distortion of digital audio from first principles, with worked examples and visual…
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-02-25 | ⏱️ Read time: 21 min read
Understanding the foundational distortion of digital audio from first principles, with worked examples and visual…
#DataScience #AI #Python
📌 How to Define the Modeling Scope of an Internal Credit Risk Model
🗂 Category: DATA SCIENCE
🕒 Date: 2026-02-25 | ⏱️ Read time: 9 min read
Dataset construction for Internal Ratings-Based (IRB) Probability of Default (PD) models
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2026-02-25 | ⏱️ Read time: 9 min read
Dataset construction for Internal Ratings-Based (IRB) Probability of Default (PD) models
#DataScience #AI #Python
📌 Scaling Feature Engineering Pipelines with Feast and Ray
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-02-25 | ⏱️ Read time: 11 min read
Utilizing feature stores like Feast and distributed compute frameworks like Ray in production machine learning systems
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-02-25 | ⏱️ Read time: 11 min read
Utilizing feature stores like Feast and distributed compute frameworks like Ray in production machine learning systems
#DataScience #AI #Python
📌 Breaking the Host Memory Bottleneck: How Peer Direct Transformed Gaudi’s Cloud Performance
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-25 | ⏱️ Read time: 9 min read
Engineering RDMA-like performance over cloud host NICs using libfabric, DMA-BUF, and HCCL to restore distributed…
#DataScience #AI #Python
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-25 | ⏱️ Read time: 9 min read
Engineering RDMA-like performance over cloud host NICs using libfabric, DMA-BUF, and HCCL to restore distributed…
#DataScience #AI #Python
📌 A Generalizable MARL-LP Approach for Scheduling in Logistics
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-02-26 | ⏱️ Read time: 17 min read
Part 1. Hybrid Solution for Dynamic Vehicle Routing — Context and Architecture
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-02-26 | ⏱️ Read time: 17 min read
Part 1. Hybrid Solution for Dynamic Vehicle Routing — Context and Architecture
#DataScience #AI #Python
❤1👍1
📌 Detecting and Editing Visual Objects with Gemini
🗂 Category: LLM APPLICATIONS
🕒 Date: 2026-02-26 | ⏱️ Read time: 34 min read
A practical guide to identifying, restoring, and transforming elements within your images
#DataScience #AI #Python
🗂 Category: LLM APPLICATIONS
🕒 Date: 2026-02-26 | ⏱️ Read time: 34 min read
A practical guide to identifying, restoring, and transforming elements within your images
#DataScience #AI #Python
❤3
Forwarded from Machine Learning with Python
📌 Designing Data and AI Systems That Hold Up in Production
🗂 Category: AUTHOR SPOTLIGHTS
🕒 Date: 2026-02-26 | ⏱️ Read time: 6 min read
A system-level perspective on architecture, agents, and responsible scale
#DataScience #AI #Python
🗂 Category: AUTHOR SPOTLIGHTS
🕒 Date: 2026-02-26 | ⏱️ Read time: 6 min read
A system-level perspective on architecture, agents, and responsible scale
#DataScience #AI #Python
📌 Take a Deep Dive into Filtering in DAX
🗂 Category: DATA ANALYSIS
🕒 Date: 2026-02-26 | ⏱️ Read time: 13 min read
Have you ever wondered what happens when you apply a filter in a DAX expression?…
#DataScience #AI #Python
🗂 Category: DATA ANALYSIS
🕒 Date: 2026-02-26 | ⏱️ Read time: 13 min read
Have you ever wondered what happens when you apply a filter in a DAX expression?…
#DataScience #AI #Python
📌 Coding the Pong Game from Scratch in Python
🗂 Category: PROGRAMMING
🕒 Date: 2026-02-27 | ⏱️ Read time: 18 min read
Implementing the classic Pong game in Python using OOP and Turtle
#DataScience #AI #Python
🗂 Category: PROGRAMMING
🕒 Date: 2026-02-27 | ⏱️ Read time: 18 min read
Implementing the classic Pong game in Python using OOP and Turtle
#DataScience #AI #Python
👍2
📌 Stop Asking if a Model Is Interpretable
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-27 | ⏱️ Read time: 6 min read
Start asking what question the explanation should answer.
#DataScience #AI #Python
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-27 | ⏱️ Read time: 6 min read
Start asking what question the explanation should answer.
#DataScience #AI #Python