AI Tools & Frameworks Directory

In this guide, you will learn the process of generating a year's worth of daily temperature readings, mimicking a seasonal curve that looks like real — all together with device-level metadata, and ready to build based on open-source frameworks.

Sales teams spend hours every day on tasks that should never see a human. Research a prospect, score them against their fit, and put it all into a CRM. These are repeatable, rule based processes AI workflows driven by multi-agent systems can do all three, with speed and consistency that no human tea...

The strongest AI voices are not just people with impressive job titles. They are researchers pushing the technical boundaries of AI. Founders building AI communities. Practitioners turning models into products. Even leaders, helping businesses understand what this technology can actually do. This be...

This tutorial covers three NLP tasks: text classification, zero-shot labelling, and question answering using Transformers.js's pipeline() API.

The AI industry has matured to the point where raw intelligence is no longer the only thing that matters. A year ago, every model release was a race to publish bigger benchmark numbers. More parameters, features and everything in between.   Today, the conversation is shifting. Developers care about ...

This article shows how to use free, open-source tools like Python and its Textstat library to build a script that automates the process of capturing "gatekeeping language" in job descriptions before publishing them.

In this article, we will go deep under the hood of Ollama's configuration engine, exploring how to fine-tune local language model parameters.

Modern data pipelines handle massive volumes of structured and unstructured data every day. As datasets grow, poorly optimized Spark jobs become slower, more expensive, and harder to scale. Common issues include long execution times, excessive shuffling, memory bottlenecks, and inefficient joins. Ef...

In this article, we cover three topics: what to visualize during training, the tools that provide those visualizations, and the methods to capture model computations directly using hooks and breakpoints.

Most AI automation content sounds useful, but then leaves you with one big question: where to start? Instead of only talking about automation, you probably want to create real-world automation workflows with minimal coding. That’s where the power of low-code platforms like n8n comes into play. Here ...

Learn how to use Mimesis library to generate a balanced, counterfactual dataset that helps analyze potential bias in your models.

Let's take a look at five more fundamental concepts that every Python developer should have in their toolkit.

Claude Cowork shifts AI from chat-based assistance to task delegation. Instead of giving users instructions, it performs actions directly on the user’s computer, files, applications, and browser workflows. Combined with Playwright MCP, Claude Desktop can open pages, click buttons, fill forms, extrac...

Alibaba’s Qwen team has unveiled Qwen3.7-Max, a flagship model built for the agent era. Unlike conventional chatbot-focused LLMs, it is designed as a foundation for autonomous AI agents that can code, debug, use tools, manage workflows, and execute long-running enterprise tasks. Alibaba claims the m...

In this tutorial, we will give Gemma 4 two new tools and watch the model decide, on its own, when to look around and when to compute.

Google Search just went from being an encyclopedia to an assistant. That’s the crux of everything Google announced in its recent I/O conference for 2026. The buzzword is “AI agents”, which now enter Google Search, its coding platforms, and even get a whole new standalone app for themselves. The idea...

Learn how to utilize Python's Mimesis library for anonymizing sensitive production data, based on a step-by-step example to try yourself.

Google Gemini’s next-generation family offering: Gemini 3.5 is here!  Gemini 3.5 Flash combines frontier intelligence with real-world action and supports high-speed agentic workflows, coding, and multimodal reasoning while maintaining the low latency expected from the Flash series. With Gemini 3.5 P...

In the world of data science, SQL still remains the powerful tool for defining the data, data manipulation, data aggregation and data analysis. While basic SQL commands are very fundamental, and everyone knows about it. If you want to be the unique in the crowd then you should know advanced features...

I have been running local models as part of my daily workflow for some time, and what surprised me most is how often local turned out to be the better choice, not a compromise.

In this article, we will explore five fundamental concepts that every Python developer should have in their toolkit.

Learn how to use Python itertools to build efficient and scalable time series features.

Here are 5 small language models that hare one important trait: they all support structured tool calling in a compact, open-weight package.

There are some obvious signs that can instantly differentiate between regular and advanced AI users. One, for instance, is the use of voice AI for daily tasks. While majority users still toil away on their keyboard for the perfect prompt, a person proficient in the use of AI now simply speaks to it....