📌 How Do Computers Actually Compute?

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-10 | ⏱️ Read time: 10 min read

A Budding Data Scientist’s Introduction to Computer Hardware

📌 Deploy a LightGBM ML Model With GitHub Actions

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-10 | ⏱️ Read time: 9 min read

A beginner’s guide to getting out of Jupyter notebooks and deploying ML models

📌 Building LLM Apps: A Clear Step-By-Step Guide

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-10 | ⏱️ Read time: 14 min read

Comprehensive Steps for Building LLM-Native Apps: From Initial Idea to Experimentation, Evaluation, and Productization

📌 From Masked Image Modeling to Autoregressive Image Modeling

🗂 Category: DEEP LEARNING

🕒 Date: 2024-06-10 | ⏱️ Read time: 5 min read

A brief review of the image foundation model pre-training objectives

📌 It’s Time to Finally Memorize those Dang Classification Metrics!

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-10 | ⏱️ Read time: 11 min read

Intuition behind the metrics and how I finally memorized them

📌 How LLMs Will Democratize Exploratory Data Analysis

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-09 | ⏱️ Read time: 19 min read

Or, When you feel your life’s too hard, just go have a talk with Claude

📌 Pandas Indexes And Headers, Have You Ever Been Confused?

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-09 | ⏱️ Read time: 8 min read

From single-level index and headers to multi-level, why and how?

📌 Hands On Optimization with Expected Improvement and Gaussian Process Regression, in Python

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-09 | ⏱️ Read time: 12 min read

A friendly guide to Expected Improvement for Global Optimization, in Python

📌 Here is what using an LLM for monsters taught me about programming

🗂 Category: PROGRAMMING

🕒 Date: 2024-06-09 | ⏱️ Read time: 9 min read

How I learned to use AI as an alternative to generate amazing random data.

📌 What “Dream Big” Meant for Data Science Innovation at LinkedIn

🗂 Category: BUSINESS

🕒 Date: 2024-06-09 | ⏱️ Read time: 10 min read

Here’s how to inspire and lead people for bigger data science projects

📌 Validating the Causal Impact of the Synthetic Control Method

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-08 | ⏱️ Read time: 11 min read

Causal AI, exploring the integration of causal reasoning into machine learning

📌 SQL Knowledge You Need For Data Science

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-08 | ⏱️ Read time: 11 min read

Topics, resources and advice for becoming proficient in SQL.

📌 Paper review – Communicative Agents for Software Development

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-08 | ⏱️ Read time: 12 min read

After reading and reviewing the Generative Agents paper, I decided to explore the world of…

📌 Python Data Analysis: What Do We Know About Modern Artists?

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-08 | ⏱️ Read time: 15 min read

Finding patterns in the media landscape with Wikipedia, Python, and NetworkX

📌 A Day in the Life of a Data Scientist

🗂 Category: CAREER ADVICE

🕒 Date: 2024-06-08 | ⏱️ Read time: 8 min read

What do I actually do all day, anyway?

📌 Tiny Time Mixers (TTM): A Powerful Zero-Shot Forecasting Model by IBM

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-08 | ⏱️ Read time: 11 min read

A new lightweight open-source foundation model

📌 Principal Component Analysis Made Easy: A Step-by-Step Tutorial

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-08 | ⏱️ Read time: 10 min read

Implement the PCA algorithm from scratch with Python

📌 What Is a Good Imputation for Missing Values?

🗂 Category: STATISTICS

🕒 Date: 2024-06-08 | ⏱️ Read time: 21 min read

My current take on what imputation should be

📌 How to Build a Generative Search Engine for Your Local Files Using Llama 3

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2024-06-08 | ⏱️ Read time: 15 min read

Use Qdrant, NVidia NIM API, or Llama 3 8B locally for your local GenAI assistant

📌 Can We Save the AI Economy?

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-10-18 | ⏱️ Read time: 23 min read

And do we want to?