As a Data Scientist, I use statistical methods such as ML algorithms in order to identify patterns and to extract knowledge from data.
📘 Introduction Data is only as useful as your ability to explore and understand it. But building an interface to analyze and visualize your DataFrame often feels like a full-blown front-end project. That’s where Streamlit saves the day. In this tutorial, you’ll learn how to build a data app...
📘 Introduction Chatbots are transforming the way we interact with data, services, and even entertainment. But building an intuitive interface for your chatbot can often feel like a front-end headache. That’s where Streamlit shines. It helps you create interactive, elegant UIs for your Python scripts—without touching HTML or CSS....
📘 Introduction Creating interactive web apps with Streamlit is incredibly easy — even if you're not a front-end developer. Once you've mastered the basics, Streamlit’s widget system becomes your playground. These widgets let users interact with your data and models in real time. In this post, you&...
📘 Introduction Data scientists and analysts often struggle to share their work interactively. Whether it's model results or beautiful visualizations, the gap between code and a usable interface can be frustrating. That's where Streamlit comes in. Streamlit is a powerful Python framework that turns your data scripts...
Introduction The Hugging Face Inference API makes it easy to send prompts to large language models (LLMs) hosted on the Hugging Face Hub. By combining this with Gradio, you can quickly build interactive chatbots and demos with a simple, web-based user interface—without worrying about backend frameworks. In this tutorial,...
Introduction The Hugging Face Inference API makes it easy to send prompts to large language models (LLMs) hosted on the Hugging Face Hub. By combining this with FastAPI—a modern Python web framework—you can build scalable, production-ready APIs that serve LLM-powered responses to your applications. In this tutorial, you’...
Introduction The Hugging Face Inference API is a powerful service that lets you interact with large language models (LLMs) hosted on the Hugging Face Hub. Whether you’re building chatbots, summarization tools, or other AI-powered applications, the Inference API makes it simple to send prompts to an LLM and receive...
Introduction When working with PySpark DataFrames, handling different data types correctly is essential for data preprocessing. Mismatched or incorrect data types can lead to errors in Spark operations such as filtering, aggregations, and machine learning workflows. In this tutorial, we’ll explore how to convert column data types in a...
Introduction The Data Science experience in Microsoft Fabric simplifies the end-to-end machine learning process by enabling users to effortlessly create, train, and deploy Machine Learning Models. In this tutorial, we will explain step-by-step how to create a Machine Learning Model in Fabric. Step 1: Sign in to Fabric First, sign...