ISAC (Intelligent Site Analysis & Capture) is a CLI tool that extracts brand design systems from live websites (fonts, colors, icons, branding) and generates production-ready Next.js projects with design tokens. Optionally replicates full landing pages. Powered by Claude AI and agent-browser.

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Phone"!==a?!0:!1},getHasLiedBrowser:function(){var a=navigator.userAgent,b=navigator.productSub,a=0<=a.toLowerCase().indexOf("firefox")?"Firefox":0<=a.toLowerCase().indexOf("opera")||0<=a.toLowerCase().indexOf("opr")?"Opera":0<=a.toLowerCase().indexOf("chrome")?"Chrome":0<=a.toLowerCase().indexOf("safari")?"Safari":0<=a.toLowerCase().indexOf("trident")?"Internet Explorer":"Other";if(("Chrome"===a||"Safari"===a||"Opera"===a)&&"20030107"!==b)return!0;b=eval.toString().length;if(37===b&& "Safari"!==a&&"Firefox"!==a&&"Other"!==a||39===b&&"Internet Explorer"!==a&&"Other"!==a||33===b&&"Chrome"!==a&&"Opera"!==a&&"Other"!==a)return!0;var c;try{throw"a";}catch(g){try{g.toSource(),c=!0}catch(d){c=!1}}return c&&"Firefox"!==a&&"Other"!==a?!0:!1},isIE:function(){return"Microsoft Internet Explorer"===naviga

Landing Page Analysis webapp for automatically analyzing areas of improvement from an open vision model.

# Web Design Homework - Web Visualization Dashboard (Latitude) ## Background Data is more powerful when we share it with others! Let's take what we've learned about HTML and CSS to create a dashboard showing off the analysis we've done.  ### Before You Begin 1. Create a new repository for this project called `Web-Design-Challenge`. **Do not add this homework to an existing repository**. 2. Clone the new repository to your computer. 3. Inside your local git repository, create a directory for the web challenge. Use a folder name to correspond to the challenge: **WebVisualizations**. 4. Add your **html** files to this folder as well as your **assets**, **Resources** and **visualizations** folders. 5. Push the above changes to GitHub or GitLab. 6. Deploy to GitHub pages. ## Latitude - Latitude Analysis Dashboard with Attitude For this homework we'll be creating a visualization dashboard website using visualizations we've created in a past assignment. Specifically, we'll be plotting [weather data](Resources/cities.csv). In building this dashboard, we'll create individual pages for each plot and a means by which we can navigate between them. These pages will contain the visualizations and their corresponding explanations. We'll also have a landing page, a page where we can see a comparison of all of the plots, and another page where we can view the data used to build them. ### Website Requirements For reference, see the ["Screenshots" section](#screenshots) below. The website must consist of 7 pages total, including: * A [landing page](#landing-page) containing: * An explanation of the project. * Links to each visualizations page. There should be a sidebar containing preview images of each plot, and clicking an image should take the user to that visualization. * Four [visualization pages](#visualization-pages), each with: * A descriptive title and heading tag. * The plot/visualization itself for the selected comparison. * A paragraph describing the plot and its significance. * A ["Comparisons" page](#comparisons-page) that: * Contains all of the visualizations on the same page so we can easily visually compare them. * Uses a Bootstrap grid for the visualizations. * The grid must be two visualizations across on screens medium and larger, and 1 across on extra-small and small screens. * A ["Data" page](#data-page) that: * Displays a responsive table containing the data used in the visualizations. * The table must be a bootstrap table component. [Hint](https://getbootstrap.com/docs/4.3/content/tables/#responsive-tables) * The data must come from exporting the `.csv` file as HTML, or converting it to HTML. Try using a tool you already know, pandas. Pandas has a nifty method approprately called `to_html` that allows you to generate a HTML table from a pandas dataframe. See the documentation [here](https://pandas.pydata.org/pandas-docs/version/0.17.0/generated/pandas.DataFrame.to_html.html) The website must, at the top of every page, have a navigation menu that: * Has the name of the site on the left of the nav which allows users to return to the landing page from any page. * Contains a dropdown menu on the right of the navbar named "Plots" that provides a link to each individual visualization page. * Provides two more text links on the right: "Comparisons," which links to the comparisons page, and "Data," which links to the data page. * Is responsive (using media queries). The nav must have similar behavior as the screenshots ["Navigation Menu" section](#navigation-menu) (notice the background color change). Finally, the website must be deployed to GitHub pages. When finished, submit to BootcampSpot the links to 1) the deployed app and 2) the GitHub repository. Ensure your repository has regular commits (i.e. 20+ commits) and a thorough README.md file ### Considerations * You may use the [weather data](Resources/cities.csv) or choose another dataset. Alternatively, you may use the included [cities dataset](Resources/cities.csv) and pull the images from the [assets folder](Resources/assets). * You must use Bootstrap. This includes using the Bootstrap `navbar` component for the header on every page, the bootstrap table component for the data page, and the Bootstrap grid for responsiveness on the comparison page. * You must deploy your website to GitHub pages, with the website working on a live, publicly accessible URL as a result. * Be sure to use a CSS media query for the navigation menu. * Be sure your website works at all window widths/sizes. * Feel free to take some liberty in the visual aspects, but keep the core functionality the same.

A permanent Hermes Agent skill that transforms any startup idea into an investor-ready kit. Chains web_search, terminal & write_file to generate 8 assets: market analysis, competitor map, pitch deck, roadmap & a Tailwind landing page. Built for Hermes Hackathon 2026.

Targeted Marketing on Social Media: Utilizing Text Analysis to Create Personalized Landing Pages

Landing page built with HTML and CSS, developed at the beginning of the second semester of the Analysis and Systems Development course, during the Front-End class.

Realestate analysis tool for Latvian market - landing page.

This is the landing page for Genetic Analysis of Population-based Association Studies Course.

This repository contains a project focused on optimizing landing page conversions through A/B testing. It includes data analysis, experiment design, and results interpretation to enhance user engagement and conversion rates.

This is a simple web app of a company's landing page. This app also have dashboard where admin can do lots of stuff e.g. add customers, view customers, do analysis etc.

A landing page featuring cryptocurrency market analysis is my project, embodying unique design and dynamic animations. Full adaptability ensures usability on any device. I invite you to appreciate frontend development in the world of cryptocurrency trends!

Welcome to my COVID-19 landing page. Here, you can find the most up-to-date information on the covid pandemic, as well as access to my own API for data analysis. Stay informed and stay safe.

Gensys is a landing page for a real time remote monitoring app that tracks power usage across buildings or companies, including grid and generator sources. It records fueling activity such as fill time, fuel and water levels, and other key metrics, while providing detailed reports and analysis to help you understand fuel usage patterns.

Latitude - Latitude Analysis Dashboard with Attitude For this homework we'll be creating a visualization dashboard website using visualizations we've created in a past assignment. Specifically, we'll be plotting weather data. In building this dashboard, we'll create individual pages for each plot and a means by which we can navigate between them. These pages will contain the visualizations and their corresponding explanations. We'll also have a landing page, a page where we can see a comparison of all of the plots, and another page where we can view the data used to build them. Website Requirements For reference, see the "Screenshots" section below. The website must consist of 7 pages total, including: A landing page containing: An explanation of the project. Links to each visualizations page. Four visualization pages, each with: A descriptive title and heading tag. The plot/visualization itself for the selected comparison. A paragraph describing the plot and its significance. A "Comparisons" page that: Contains all of the visualizations on the same page so we can easily visually compare them. Uses a bootstrap grid for the visualizations. The grid must be two visualizations across on screens medium and larger, and 1 across on extra-small and small screens. A "Data" page that: Displays a responsive table containing the data used in the visualizations. The table must be a bootstrap table component. The data must come from exporting the .csv file as HTML, or converting it to HTML. Try using a tool you already know, pandas. Pandas has a nifty method approprately called to_html that allows you to generate a HTML table from a pandas dataframe. See the documentation here The website must, at the top of every page, have a navigation menu that: Has the name of the site on the left of the nav which allows users to return to the landing page from any page. Contains a dropdown on the right of the navbar named "Plots" which provides links to each individual visualization page. Provides two more links on the right: "Comparisons" which links to the comparisons page, and "Data" which links to the data page. Is responsive (using media queries). The nav must have similar behavior as the screenshots "Navigation Menu" section (notice the background color change). Finally, the website must be deployed to GitHub pages. When finished, submit to BootcampSpot the links to 1) the deployed app and 2) the GitHub repository. Considerations You may use the weather data or choose another dataset. Alternatively, you may use the included cities dataset and pull the images from the assets folder. You must use bootstrap. This includes using the bootstrap navbar component for the header on every page, the bootstrap table component for the data page, and the bootstrap grid for responsiveness on the comparison page. You must deploy your website to GitHub pages, with the website working on a live, publicly accessible URL as a result. Be sure to use a CSS media query for the navigation menu. Be sure your website works at all window widths/sizes. Feel free to take some liberty in the visual aspects, but keep the core functionality the same.

Background Data is more powerful when we share it with others! Let's take what we've learned about HTML and CSS to create a dashboard showing off the analysis we've done. Before You Begin Create a new repository for this project called Web-Design-Challenge. Do not add this homework to an existing repository. Clone the new repository to your computer. Inside your local git repository, create a directory for the web challenge. Use a folder name to correspond to the challenge: WebVisualisations. Add your html files to this folder as well as your assets, Resources and visualisations folders. Push the above changes to GitHub or GitLab. Deploy to GitHub pages. Latitude - Latitude Analysis Dashboard with Attitude For this homework we'll be creating a visualisation dashboard website using visualisations we've created in a past assignment. Specifically, we'll be plotting weather data. In building this dashboard, we'll create individual pages for each plot and a means by which we can navigate between them. These pages will contain the visualisations and their corresponding explanations. We'll also have a landing page, a page where we can see a comparison of all of the plots, and another page where we can view the data used to build them. Website Requirements For reference, see the "Screenshots" section below. The website must consist of 7 pages total, including: A landing page containing: An explanation of the project. Links to each visualisations page. There should be a sidebar containing preview images of each plot, and clicking an image should take the user to that visualisation. Four visualisation pages, each with: A descriptive title and heading tag. The plot/visualisation itself for the selected comparison. A paragraph describing the plot and its significance. A "Comparisons" page that: Contains all of the visualisations on the same page so we can easily visually compare them. Uses a Bootstrap grid for the visualisations. The grid must be two visualisations across on screens medium and larger, and 1 across on extra-small and small screens. A "Data" page that: Displays a responsive table containing the data used in the visualisations. The table must be a bootstrap table component. Hint The data must come from exporting the .csv file as HTML, or converting it to HTML. Try using a tool you already know, pandas. Pandas has a nifty method appropriately called to_html that allows you to generate a HTML table from a pandas dataframe. See the documentation here The website must, at the top of every page, have a navigation menu that: Has the name of the site on the left of the nav which allows users to return to the landing page from any page. Contains a dropdown menu on the right of the navbar named "Plots" that provides a link to each individual visualisation page. Provides two more text links on the right: "Comparisons," which links to the comparisons page, and "Data," which links to the data page. Is responsive (using media queries). The nav must have similar behaviour as the screenshots "Navigation Menu" section (notice the background color change). Finally, the website must be deployed to GitHub pages. When finished, submit to BootcampSpot the links to 1) the deployed app and 2) the GitHub repository. Considerations You may use the weather data or choose another dataset. Alternatively, you may use the included cities dataset and pull the images from the assets folder. You must use Bootstrap. This includes using the Bootstrap navbar component for the header on every page, the bootstrap table component for the data page, and the Bootstrap grid for responsiveness on the comparison page. You must deploy your website to GitHub pages, with the website working on a live, publicly accessible URL as a result. Be sure to use a CSS media query for the navigation menu. Be sure your website works at all window widths/sizes. Feel free to take some liberty in the visual aspects, but keep the core functionality the same. Bonuses Use a different dataset! The requirements above still hold, but make it your own. Use a Bootstrap theme to customise your website. You may use a tool like Bootswatch. Make it look snazzy, give it some attitude. If using this, be sure you also meet all of the requirements listed above. Add extra visualisations! The more comparisons the better, right? Use meaningful glyphicons next to links in the header. Have visualisation navigation on every visualisations page with an active state. See the screenshots below. Screenshots This section contains screenshots of each page that must be built, at varying screen widths. These are a guide; you can meet the requirements without having the pages look exactly like the below images. Landing page Large screen: Small screen:  Comparisons page Large screen: Small screen: Data page Large screen: Small screen: Visualisation pages You'll build four of these, one for each visualisation. Here's an example of one: Large screen: Small screen: Navigation menu Large screen: Small screen: Copyright © 2021 Trilogy Education Services, LLC, a 2U, Inc. brand. Confidential and Proprietary. All Rights Reserved.

Sentiment Analysis Landing Page Project

A/B Test, Z-test, Logistic Regression modelling and analysis for a E-Commerce company's landing page

No description available

No description available

macbase — Chess Analysis for Mac (Download & Landing Page)

A/B Testing & User Behavior Analysis for Landing Page Optimization

This analysis provided the green light for a full-scale site migration, transforming "lost traffic" into "engaged customers" and ensuring marketing expenditure was no longer being wasted on a leaking funnel.

Landing Page for Medical Professionals interested in improving their medical analysis using Deep learning tools

ERP & Business Process Analysis focused student portfolio landing page built with HTML, CSS and Vanilla JavaScript.

AI-Powered Test Case Analysis Tool for QA Engineers - Interactive landing page with test case generation, categorization, and export functionality

Marketron: A sleek, responsive landing page for an AI-powered market analysis service. Built with Astro, React, and modern web technologies.

A beginner-friendly phishing awareness simulation project using GoPhish. Includes email templates, landing pages, SMTP setup, campaign execution, and results analysis.

AB test results for the impact of a new landing page on the conversion rate as part of the Udacity advanced data analysis nanodegree

Landing page for the paper "On the Role of Semantic Proto-roles in Semantic Analysis: What do LLMs know about agency?" at ACL 2025.