Articles About Machine Learning

How to Create Images Using Stable Diffusion Web UI

Launching the Stable Diffusion Web UI can be done in one command. After that, you can control the image generation pipeline from a browser. The pipeline has a lot of moving parts and all are important in one way or another. To effectively command Stable Diffusion to generate images, you should recognize the widgets from your browser and know what they can do. In this post, you will learn the many components in the Stable Diffusion Web UI and how […]

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A Technical Introduction to Stable Diffusion

The introduction of GPT-3, particularly its chatbot form, i.e. the ChatGPT, has proven to be a monumental moment in the AI landscape, marking the onset of the generative AI (GenAI) revolution. Although prior models existed in the image generation space, it’s the GenAI wave that caught everyone’s attention. Stable Diffusion is a member of the GenAI family for image generation. It is known for its possibility to customization, freely available to run on your own hardware, and actively improving. It […]

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Brief Introduction to Diffusion Models for Image Generation

The advance of generative machine learning models makes computers capable of creative work. In the scope of drawing pictures, there are a few notable models that allow you to convert a textual description into an array of pixels. The most powerful models today are part of the family of diffusion models. In this post, you will learn how this kind of model works and how you can control its output. Let’s get started. Brief Introduction to Diffusion Models for Image […]

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Unfolding Data Stories: From First Glance to In-Depth Analysis

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 into the process of data-driven storytelling, where every visualization, every statistical test, and every hypothesis forms a part of a larger narrative. This blog post […]

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The Da Vinci Code of Data: Mastering The Data Science Mind Map

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 Leonardo da Vinci masterfully blended scientific observation with artistic genius, we will explore how the art of storytelling in data science can illuminate insights with […]

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Finding Value with Data: The Cohesive Force Behind Luxury Real Estate Decisions

The real estate industry is a vast network of stakeholders including agents, homeowners, investors, developers, municipal planners, and tech innovators, each bringing unique perspectives and objectives to the table. Within this intricate ecosystem, data emerges as the critical element that binds these diverse interests together, facilitating collaboration and innovation. PropTech, or Property Technology, illustrates this synergy by applying information technology to real estate, transforming how properties are researched, bought, sold, and managed through the power of data science. From its […]

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Harmonizing Data: A Symphony of Segmenting, Concatenating, Pivoting, and Merging

In the world of data science, where raw information swirls in a cacophony of numbers and variables, lies the art of harmonizing data. Like a maestro conducting a symphony, the skilled data scientist orchestrates the disparate elements of datasets, weaving them together into a harmonious composition of insights. Welcome to a journey where data transcends mere numbers and, instead, transforms into a vibrant melody of patterns and revelations. Let’s explore the intricacies of segmenting, concatenating, pivoting, and merging data using […]

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Beyond SQL: Transforming Real Estate Data into Actionable Insights with Pandas

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 applying SQL-like functions within Python to dissect and understand data, using the Ames Housing dataset as your canvas. The Ames Housing dataset, a comprehensive compilation […]

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Skewness Be Gone: Transformative Tricks for Data Scientists

Data transformations enable data scientists to refine, normalize, and standardize raw data into a format ripe for analysis. These transformations are not merely procedural steps; they are essential in mitigating biases, handling skewed distributions, and enhancing the robustness of statistical models. This post will primarily focus on how to address skewed data. By focusing on the ‘SalePrice’ and ‘YearBuilt’ attributes from the Ames housing dataset, we will provide examples of positive and negative skewed data and illustrate ways to normalize […]

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Spotting the Exception: Classical Methods for Outlier Detection in Data Science

Outliers are unique in that they often don’t play by the rules. These data points, which significantly differ from the rest, can skew your analyses and make your predictive models less accurate. Although detecting outliers is critical, there is no universally agreed-upon method for doing so. While some advanced techniques like machine learning offer solutions, in this post, we will focus on the foundational Data Science methods that have been in use for decades. Let’s get started. Spotting the Exception: […]

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