Essential Python Libraries for Data Science
Author(s): Raj kumar Originally published on Towards AI. In Part 1, we built the foundations of the data pipeline. We loaded a real dataset, structured it using Pandas, selected relevant features, and performed numerical transformations using NumPy. By the end of Step …
What If I Told You the Most Powerful Algorithm in Statistics Is Just… Guessing?
Author(s): Kamrun Nahar Originally published on Towards AI. I stared at the Wikipedia page for MCMC for forty-five minutes. The page had seventeen Greek letters in the first paragraph. I understood exactly zero of them. Three years later, I can tell you …
Your Sentence Has a Secret Structure. Here’s How GPT Sees It.
Author(s): Rohini Joshi Originally published on Towards AI. Image Generated by ChatGPT The sentence “dog bites man” and “man bites dog” contain the exact same words. A Transformer without positional encoding would treat them as identical. Here’s how modern LLMs learn word …
What RAGAS Doesn’t Tell You — RAG Evaluation From Scratch With Ollama
Author(s): Vikram Bhat Originally published on Towards AI. Evaluating a RAG Pipeline From Scratch — No RAGAS, No OpenAI, Fully Local How to build a reusable RAG evaluator using Ollama and LLM-as-judge that actually tells you where your pipeline breaks Rag Evaluation …
Cutting Batch Release from 14 Days to 3: A Case Study in Multi-Agent AI for Pharmaceutical Manufacturing
Author(s): Saif Ali Kheraj Originally published on Towards AI. How agentic AI architectures can compress decision cycles in regulated manufacturing with a practical implementation blueprint using CrewAI. Every contract pharmaceutical manufacturer faces the same operational bottleneck. After a medicine batch completes production …
JSON Tool Calling Is Dead. Here’s What Replaces It
Author(s): MKWriteshere Originally published on Towards AI. Anthropic just made code-based tool orchestration the default path forward. Hugging Face saw this coming in December 2024. Here’s a pattern you’ll notice if you watch the AI industry closely enough: the open-source community figures …
You probably don’t need a Vector Database (Yet) for your RAG
Author(s): Thomas Reid Originally published on Towards AI. Numpy and/or SciKit-Learn might meet all your retrieval needs Right now, off the back of Retrieval Augmented Generation (RAG), vector databases are getting a lot of attention in the AI world. Image by Nano …
The 6 Essential Prompt Engineering Techniques: How to Get 10× Better Results from the Same LLM
Author(s): TANVEER MUSTAFA Originally published on Towards AI. Understanding Zero-Shot, Few-Shot, Chain-of-Thought, Self-Consistency, Tree of Thoughts, and ReAct You ask an LLM to analyze market trends. It gives a vague, generic response. Your colleague asks the same model with a different prompt …
Context Engineering: The 6 Techniques That Actually Matter in 2026 ( A Comprehensive Guide )
Author(s): Divy Yadav Originally published on Towards AI. Prompt engineering is dead. Context engineering is how production systems work now. Your RAG system returns perfect chunks. Your prompt is beautifully crafted But The LLM still hallucinates. Photo by AuthorThe article discusses the …
Latent Space: The Most Important Place That Doesn’t Exist
Author(s): Ampatishan Sivalingam Originally published on Towards AI. How AI navigates invisible dimensions to understand reality, and why you should care Every time you prompt an AI to create a “cyberpunk cat playing jazz,” you are navigating a multi-dimensional map you cannot …
20 Must Visit SQL Questions For Interviews
Author(s): Ananya Originally published on Towards AI. Q1. Find the total number of orders placed by a customer (101) in a day. Table: Order_Details cust_id | order_id | order_date Code: select date_trunc(‘day’, order_date) as day, cust_id as customers count(distinct order_id) as orders …
What Are World Models? The Blueprint for the Next Decade of AI
Author(s): Ampatishan Sivalingam Originally published on Towards AI. We built machines that can talk. Now we’re building machines that can think, plan, and imagine, before they ever act. A toddler reaches for a stack of wooden blocks. She doesn’t just see the …
The 6 Optimization Algorithms: How AI Learns to Learn 10× Faster with 50% Less Memory
Author(s): TANVEER MUSTAFA Originally published on Towards AI. The 6 Optimization Algorithms: How AI Learns to Learn 10× Faster with 50% Less Memory You’re training a language model with 175 billion parameters. Image generated by Author using AIThis article explores six optimization …
GPU and CPU Utilization While Running Open-Source LLMs Locally using Ollama
Author(s): Muaaz Originally published on Towards AI. Large Language Models (LLMs) are powerful, but running them locally requires significant hardware resources. Many users rely on open-source models due to their accessibility, as closed source models often come with restrictive licensing and high …
I Analyzed 5,000 DAX Measures. Here Are The 5 Patterns That Kill Performance.
Author(s): Gulab Chand Tejwani Originally published on Towards AI. 18 seconds for one measure. The dashboard was unusable. I analyzed 5,247 DAX measures to find what kills performance. 78% had these 5 patterns. Fix one, get 14x faster. He clicks “Refresh” on …
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