ControlNet is a neural network that can improve image generation in Stable Diffusion by adding extra conditions. This allows users to have more control over the images generated. Instead of trying out different prompts, the ControlNet models enable users to generate consistent images with just one prompt. In this post, you will learn how to […]
Inpainting and outpainting have long been popular and well-studied image processing domains. Traditional approaches to these problems often relied on complex algorithms and deep learning techniques yet still gave inconsistent outputs. However, recent advancements in the form of Stable diffusion have reshaped these domains. Stable diffusion now offers enhanced efficacy in inpainting and outpainting while […]
Stable Diffusion’s latest models are very good at generating hyper-realistic images, but they can struggle with accurately generating human faces. We can experiment with prompts, but to get seamless, photorealistic results for faces, we may need to try new methodologies and models. In this post, we will explore various techniques and models for generating highly […]
The path to uncovering meaningful insights often starts with a single step: looking at the data before asking questions. This journey through the Ames Housing dataset is more than an exploration; it’s a narrative about the hidden stories within numbers, waiting to be told. Through a “Data First Approach,” we invite you to dive deep […]
Data Science embodies a delicate balance between the art of visual storytelling, the precision of statistical analysis, and the foundational bedrock of data preparation, transformation, and analysis. The intersection of these domains is where true data alchemy happens – transforming and interpreting data to tell compelling stories that drive decision-making and knowledge discovery. Just as […]
In the realm of data analysis, SQL stands as a mighty tool, renowned for its robust capabilities in managing and querying databases. However, Python’s pandas library brings SQL-like functionalities to the fingertips of analysts and data scientists, enabling sophisticated data manipulation and analysis without the need for a traditional SQL database. This exploration delves into […]
The Chi-squared test for independence is a statistical procedure employed to assess the relationship between two categorical variables – determining whether they are associated or independent. In the dynamic realm of real estate, where a property’s visual appeal often impacts its valuation, the exploration becomes particularly intriguing. But how often do you associate a house’s […]
When working with datasets like the Ames Housing dataset, understanding and preparing your data is the first crucial step towards meaningful analysis. This post will walk you through essential data preparation techniques, starting with how to use the data dictionary effectively. We’ll look at identifying different types of variables—categorical and numerical—and tackle the common issue […]
ChatGPT as a Large Language Model, is well-known for understanding human languages. Instead of asking ChatGPT for an answer you don’t know, you can make it work on existing information while leveraging the natural language understanding (NLU) capability. In this post, you will learn How to make ChatGPT produce a summary from a long text […]
In this era of information overload, summarizing plays a crucial role in extracting meaningful information from large amounts of data. It is not only time-saving but also facilitates quick decision-making. However, manual summarization techniques of hiring human experts to read, analyze and summarize the data have become obsolete due to the exponential growth of data. […]
