Beginner

Auto Added by WPeMatico

Top 10 GitHub Repositories Trending in July 2026 (AI, ML & GenAI Edition)

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, GitHub, Machine Learning

If you’ve spent any time on GitHub Trending this month, you’ve probably noticed a pattern: it isn’t research papers turning into repositories anymore, it’s agents. Coding agents, pentesting agents, trading agents, and the infrastructure that ties them all together. We tracked star growth, momentum, and real-world impact to identify the ten repositories that mattered most […]

Top 10 GitHub Repositories Trending in July 2026 (AI, ML & GenAI Edition) Read More »

How to connect MCP servers with Claude (Claude desktop and Claude Code)

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, LLMs, Python

Connecting MCP servers to Claude allows it to work with external tools, files, databases, repositories, and other systems instead of operating only within the chat window. The setup differs slightly between Claude Desktop and Claude Code, but both can be configured in just a few steps. In this article, you’ll learn how to connect MCP

How to connect MCP servers with Claude (Claude desktop and Claude Code) Read More »

GPT-5.6 Sol vs Claude Fable 5: Benchmarks, Pricing & Hands-On

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, ChatGPT, LLMs

GPT-5.6 Sol and Claude Fable 5 are currently fighting for the frontier-model crown. Fable 5 holds a slight edge in general intelligence, while Sol hits back with stronger coding performance, faster execution and much lower pricing. In fact, GPT-5.6 Sol is priced closer to Claude Opus 4.8 than to Fable 5, which makes this comparison

GPT-5.6 Sol vs Claude Fable 5: Benchmarks, Pricing & Hands-On Read More »

Inside the Claude Fable 5 System Prompt: A Full Breakdown

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, LLMs, prompt engineering

THE GIST ▸ What it is: A 3,826-line system prompt steering Claude Fable 5 inside the Claude app, pulled from a public GitHub archive. ▸ What’s in it: Rules about safety, tone and restraint. ▸ Why it matters: it shows a frontier “AI” is far more an engineered rulebook than a mysterious mind. Before your

Inside the Claude Fable 5 System Prompt: A Full Breakdown Read More »

What is Meta Prompting and How does it work?

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, LLMs, prompt engineering

Prompts shape every interaction with a large language model. Clear instructions produce focused, useful responses, while vague ones often lead to inconsistent results. This becomes harder when teams need the same task completed repeatedly in a fixed format, tone, or structure. Meta-prompting asks the model to design a reusable prompt, template, checklist, or workflow before

What is Meta Prompting and How does it work? Read More »

Handling Imbalanced Classification: What Works Better Than SMOTE

Advanced, ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, Machine Learning

Most real-world classification problems are imbalanced. Fraud, disease, churn, and defects are rare by nature. Standard classifiers chase accuracy, so they quietly ignore the very class you care about. For years, SMOTE was the reflex fix that everyone reached for first. But SMOTE often fails on the messy, high-dimensional data that production systems actually see.

Handling Imbalanced Classification: What Works Better Than SMOTE Read More »

RAG Evaluation Frameworks Compared: RAGAS vs TruLens vs DeepEval

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, LLMs, RAG

LLMs are getting stronger every day, and building a RAG pipeline has never been easier. Knowing whether it actually works is not. Most teams ship a RAG system, see decent-looking answers, and call it done, until users hit hallucination, missing context, or irrelevant chunks. That’s where evaluation frameworks come in. RAGAS, TruLens, and DeepEval are

RAG Evaluation Frameworks Compared: RAGAS vs TruLens vs DeepEval Read More »

Loop Engineering for AI Agents: How /loop is Changing AI Workflows 

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, LLMs

AI agents are moving from one-time assistants to persistent workers that can repeat tasks, monitor changes, run checks, update workflows, and return with results. Instead of prompting an LLM once and deciding every next step manually, teams can now use AI agents that keep working (on a Loop) until a goal or stop condition is

Loop Engineering for AI Agents: How /loop is Changing AI Workflows  Read More »

DeepSeek DSpark: The Speculative Decoding Trick Behind 400% Faster LLM 

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, LLMs, Research Paper

DeepSeek’s new DSpark module brings speculative decoding to DeepSeek-V4. It might look like a niche inference tweak, but in production it boosted per-user generation speed by 60 to 85 percent with no drop in model quality. What sets DSpark apart is that it tackles two longstanding problems at once, weak draft quality and the waste

DeepSeek DSpark: The Speculative Decoding Trick Behind 400% Faster LLM  Read More »

YOLO26 Tutorial: Object Detection, Pose Estimation & More

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, Computer vision, Machine Learning

Looking to model to implement pose estimation? I know something that can perform detection, instance segmentation, pose estimation and classification, all of that in real-time. Yes, I’m talking about the YOLO26 from ultralytics.  It can aid security systems or can be fine-tuned to detect even smaller objects. Wondering how to get started? No worries, we’ll

YOLO26 Tutorial: Object Detection, Pose Estimation & More Read More »