In 2025, analysts shifted from building monolithic dashboards to creating composable data products, turning repeated analyses into reusable building blocks.  #statology

Learn Docker by doing with five beginner-friendly projects covering hosting, multi-container apps, CI, and monitoring.

Discover the data skills that truly mattered to hiring managers in 2025 beyond technical tools.  #statology

In 2025, “using AI” no longer just means chatting with a model, and you’ve probably already noticed that shift yourself. #teachthemachine

Best OCR and vision language models you can run locally that transform documents, tables, and diagrams into flawless markdown copies with benchmark-crushing accuracy.

This article is divided into three parts; they are: • Understanding the Architecture of Llama or GPT Model • Creating a Llama or GPT Model for Pretraining • Variations in the Architecture The architectur... #teachthemachine

How can we reason with uncertainty and make smarter decisions from data? This article explains the key probability ideas in data science.

Learn how to use conditional formatting in Excel with practical examples from basic highlighting to advanced formula-driven rules.  #statology

How AI Cuts Costs and Adds Value for Data Science Workflows (Sponsored) #teachthemachine

Looking ahead to 2026, the most impactful trends are not flashy frameworks but structural changes in how data pipelines are designed, owned, and operated.

Data leakage is an often accidental problem that may happen in machine learning modeling. #teachthemachine

This article explains how Gistr transforms the way data professionals interact with their most valuable asset: their accumulated knowledge.

This is a list of top LLM and VLMs that are fast, smart, and small enough to run locally on devices as small as a Raspberry Pi or even a smart fridge.

Discover which statistical methods dominate healthcare, finance, tech, retail, and sports analytics, and why these industry-method pairings became indispensable standards.  #statology

Machine learning models possess a fundamental limitation that often frustrates newcomers to natural language processing (NLP): they cannot read. #teachthemachine

"Maybe next quarter" is the most expensive phrase in data strategy. Silos inflate time-to-insight, waste top-tier talent, and kill models before they're built. Here’s how cloud + AI automation eliminate the silo tax: https://t.co/xqXo0PKTsY In #partnership with Ingram Micro

This article is divided into four parts; they are: • How Logits Become Probabilities • Temperature • Top- k Sampling • Top- p Sampling When you ask an LLM a question, it outputs a vector of logits. #teachthemachine

Your data scientists aren't slow. Your data architecture is. Up to 80% of their time is lost to cleaning, wrangling, and reconciling siloed data. That's not a delay cost. It's an innovation tax. Read more on the real cost of inaction: https://t.co/xqXo0PKTsY In #partnership with

From daily weather measurements or traffic sensor readings to stock prices, time series data are present nearly everywhere. #teachthemachine

Spending too much time on repetitive tasks? These Python scripts will help you automate the mundane stuff that drains your productivity.