📌 AI Feels Easier Than Ever, But Is It Really?

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-10-15 | ⏱️ Read time: 9 min read

The 4 big challenges of building AI products

📌 Evaluating synthetic data

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-10-14 | ⏱️ Read time: 9 min read

Assessing plausibility and usefulness of data we generated from real data

📌 How to Choose the Best ML Deployment Strategy: Cloud vs. Edge

🗂 Category:

🕒 Date: 2024-10-14 | ⏱️ Read time: 17 min read

The choice between cloud and edge deployment could make or break your project

📌 Florence-2: Advancing Multiple Vision Tasks with a Single VLM Model

🗂 Category:

🕒 Date: 2024-10-14 | ⏱️ Read time: 8 min read

A Guided Exploration of Florence-2’s Zero-Shot Capabilities: Captioning, Object Detection, Segmentation and OCR.

📌 PyTorch Optimizers Aren’t Fast Enough. Try These Instead

🗂 Category: DATA SCIENCE

🕒 Date: 2024-10-14 | ⏱️ Read time: 12 min read

These 4 advanced optimizers will open your mind.

📌 How to Set Bid Guardrails in PPC Marketing

🗂 Category: DATA SCIENCE

🕒 Date: 2024-10-14 | ⏱️ Read time: 14 min read

Without controls, bidding algorithms can be quite volatile. Learn how to protect performance through adding…

📌 Product-Oriented ML: A Guide for Data Scientists

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-10-14 | ⏱️ Read time: 30 min read

How to build ML products users love

📌 lintsampler: a new way to quickly get random samples from any distribution

🗂 Category: PROBABILITY

🕒 Date: 2024-10-14 | ⏱️ Read time: 5 min read

lintsampler is a pure Python package that can easily and efficiently generate random samples from…

📌 Bringing Structure to Your Data

🗂 Category:

🕒 Date: 2024-10-14 | ⏱️ Read time: 13 min read

Testing assumptions with path models

📌 How to Perform A/B Testing with Hypothesis Testing in Python: A Comprehensive Guide

🗂 Category: DATA SCIENCE

🕒 Date: 2024-10-13 | ⏱️ Read time: 11 min read

A Step-by-Step Guide to Making Data-Driven Decisions with Practical Python Examples

📌 Recruiting vs. Interviewing for Data Roles in Diverse Markets

🗂 Category: CAREER ADVICE

🕒 Date: 2024-10-13 | ⏱️ Read time: 12 min read

Factors of success in recruiting and interviewing after applying for 150+ positions and reviewing 500+…

📌 Top 5 Principles for Building User-Friendly Data Tables

🗂 Category: DATA ENGINEERING

🕒 Date: 2024-10-13 | ⏱️ Read time: 9 min read

Designing intuitive and reliable tables that your data team will love

📌 Linear Discriminant Analysis (LDA)

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-10-12 | ⏱️ Read time: 13 min read

Discover how LDA helps identify critical data features

📌 Upgrading to Prefect Push Workers on AWS ECS

🗂 Category: DATA ENGINEERING

🕒 Date: 2024-10-12 | ⏱️ Read time: 6 min read

Upgrade from Prefect 2.0 to 3.0 and use the new Push Work Pools that greatly…

📌 Why the 2024 Nobel Prize in (AI for) Chemistry Matters So Much

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-10-12 | ⏱️ Read time: 6 min read

To Demis Hassabis and John Jumper, from DeepMind, and to David Baker, leader of the…

📌 Improve Your RAG Context Recall by 95% with an Adapted Embedding Model.

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2024-10-12 | ⏱️ Read time: 11 min read

Step by Step Model Adaptation Code and Results Attached.

📌 Gaussian Naive Bayes, Explained: A Visual Guide with Code Examples for Beginners

🗂 Category: DATA SCIENCE

🕒 Date: 2024-10-12 | ⏱️ Read time: 8 min read

Bell-shaped assumptions for better predictions

📌 Bursting the AI Hype Bubble Once and for All

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-10-12 | ⏱️ Read time: 11 min read

Misinformation and poor research: a case study

📌 Common Misconceptions About Data Science

🗂 Category: CAREER ADVICE

🕒 Date: 2024-10-11 | ⏱️ Read time: 7 min read

Data science advice that you should question

📌 Understanding Automatic Differentiation in JAX: A Deep Dive

🗂 Category: DEEP LEARNING

🕒 Date: 2024-10-11 | ⏱️ Read time: 12 min read

Unleashing the Gradient: How JAX Makes Automatic Differentiation Feel Like Magic

📌 A Mixed-Methods Approach to Offline Evaluation of News Recommender Systems

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-10-11 | ⏱️ Read time: 8 min read

Combining reader feedback from surveys with behavioral click data to optimize content personalization.