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Image by Author   # Introduction  You might have trained countless machine learning models at university or on the job, but have you ever deployed one so that anyone can use it through an API or a web app? Deployment is where models become products, and it’s one of the most valuable (and underrated) skills in modern ML. In this article, we will explore 10 GitHub repositories to master machine learning deployment. These community-driven projects, examples, courses, and curated resource lists will help you learn how to package models, expose them via APIs, deploy them to the cloud, and build real-world…

Mistral AI’s latest announcement introduces DevStral 2 (123B parameters), DevStral Small 2 (24B), and the Mistral Vibe CLI, a terminal-native coding assistant built for agentic coding tasks. Both models are fully open source and tuned for production workflows, while the new Vibe CLI brings project-aware editing, code search, version control, and execution directly into the terminal. Together, these updates aim to speed up developer workflows by making large-scale code refactoring, bug fixes, and feature development more automated, and in this guide we’ll outline the technical capabilities of each tool and provide hands-on examples to get started. What is DevStral 2?…

Effective sales forecasting is the key to success for almost every business. However, creating accurate forecasts that reflect reality can feel like ‘mission impossible.’ That’s why we’ve used our experience developing sales-focused software to put together five tips that will help you forecast more accurately. Why Sales Forecasting Is Key In Business? Before we get to the tips, let’s take a moment to focus on a key question. Why is sales forecasting important? In truth, it’s not important. It’s crucial — because it helps you predict the revenue you can expect to generate within a certain timeframe.  You can then…

Image by Author   # Introduction  Agentic AI systems can break down complex tasks, use tools, and make decisions across multiple steps to achieve goals. Unlike simple chatbots that respond to single queries, agents plan, execute, and adapt their approach based on results. This capability opens possibilities for automation and problem-solving that weren’t feasible with earlier AI systems. Building effective agents requires understanding how to give AI systems agency while maintaining control and reliability. Here are seven steps to master agentic AI development.   # Step 1: Understanding the Core Agent Loop  Every agent follows a basic cycle: observe the current state,…

OpenAI models have evolved drastically over the past few years. The journey began with GPT-3.5 and has now reached GPT-5.1 and the newer o-series reasoning models. While ChatGPT uses GPT-5.1 as its primary model, the API gives you access to many more options that are designed for different kinds of tasks. Some models are optimized for speed and cost, others are built for deep reasoning, and some specialize in images or audio. In this article, I will walk you through all the major models available through the API. You will learn what each model is best suited for, which type…

The world has forgotten how to wait. And this lack of patience is putting businesses under strain. Customers expect queries to get an instant response — and if a company fails to deliver, they’ll often lose the customer for good. Where has this expectation come from? In no small part, it’s down to the use of AI in customer services. And algorithms that can respond to customers 24-7-365. If you’re yet to join the trend, we suggest you read this article, then consider your next steps. AI in Customer Service: Why’s It Important? Customers run into problems every day. When…

Image by Author   # Introduction  Are we all in a race to the bottom created by ourselves? Data professionals have been employed for years to develop large language models (LLMs). Now, the number of open data positions seems to shrink daily. Of those advertised, most seem quite abysmal. By abysmal, I don’t mean too-low salaries or unreasonable technical expectations from candidates. No, I mean those vague phrases: “Comfortable working with AI productivity tools,” “Able to ship high volumes of code,” or “Strong prompt-engineering skills a plus.” Translation: A chatbot is your main coding partner, there will be no mentorship, no…

The majority of people build machine learning models in an experimental or research setting, which is appropriate for exploration. It is not until you start to deploy it within real applications that you’ll see the actual value, for instance, a web application requesting predictions from your model, or a backend application needing to make real-time decisions based on your trained model. You want a simple, reliable way to expose your trained machine learning model as a web service, that is to say, an API. The FastAPI is a perfect choice for this task.  What is FastAPI? FastAPI is a Python…

With 2020 fading over the horizon, we can finally reflect on ‘what was’ versus ‘what could have been.’ It was undoubtedly the year of many upended plans, with countless surprises and course-changes along the way. But there’s one resounding takeaway from the last twelve months. And it’s unlikely to change this year: JavaScript has grown in profile and popularity, with machine learning one domain where the programming language has found an unlikely home. Let’s look at how Javascript prospered in 2020 — and share some predictions for what 2021 might hold. From Simple Scripts to Machine Learning JavaScript hails from…

Sponsored Content     Language models continue to grow larger and more capable, yet many teams face the same pressure when trying to use them in real products: performance is rising, but so is the cost of serving the models. High quality reasoning often requires a 70B to 400B parameter model. High scale production workloads require something far faster and far more economical. This is why model distillation has become a central technique for companies building production AI systems. It lets teams capture the behavior of a large model inside a smaller model that is cheaper to run, easier to…