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Building My AI and Machine-Learning Portfolio Website with Flask

Safi Ullah explains how he built a Python and Flask portfolio for machine-learning and computer-vision projects, from its database-backed admin area to PythonAnywhere deployment.
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“How do I stand out from thousands of other applicants?” Safi Ullah’s answer was to build a portfolio website from scratch: a Python-centered showcase for his machine-learning and computer-vision projects, deployed as a Flask application on PythonAnywhere. The walkthrough below follows his reported design and implementation; it is a personal build account, not proof that a custom website improves hiring outcomes.

Why build a custom portfolio?

Ullah says he wanted a place to present projects to prospective employers and chose to build it himself because he works in Python and wanted control over how his work was showcased. That makes Flask a personally suitable choice in this account, not a universal recommendation. Career advice from Springboard likewise treats portfolios as something candidates can make with a builder, a no-code platform, or code, and emphasizes showing work that reflects their experience and motivation.

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The practical choice is less about which option is best in the abstract and more about the work you want to take on. A custom application allows a Python backend and tailored project pages, but leaves you responsible for implementation, hosting, and maintenance. A builder may make routine content updates more convenient. Whichever route you choose, the projects and their explanation—not the mere existence of a bespoke site—need to make your experience legible.

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The stack and application structure

Ullah describes an application built with Python 3.x and Flask, using SQLite in development and PostgreSQL in production. SQLAlchemy serves as the ORM. The front end uses HTML5, CSS3, and vanilla JavaScript; Resend handles contact-form email; and Flask-WTF provides CSRF protection. He also reports rate limiting for the form. The app was deployed on PythonAnywhere.

Layer Reported choice Role in the build
Application Python 3.x and Flask Server-rendered portfolio and application routes
Data SQLite for development; PostgreSQL in production Stores portfolio content through SQLAlchemy
Front end HTML5, CSS3, vanilla JavaScript Templates, styling, and client-side interactions
Email and form protections Resend, Flask-WTF CSRF protection, and rate limiting Contact-form email delivery and reported safeguards
Hosting PythonAnywhere Deployment through a WSGI configuration

The author presents Flask as a fit for someone already working in Python who wants a custom project showcase. His comparisons with WordPress and Wix are his own assessments of control, Python fit, SEO control, and perceived lightness; they are not results from a controlled comparison. Before choosing a custom build, account for the work of maintaining the app and its hosting as well as the freedom to shape it.

How the portfolio is organized

The reported codebase uses an application factory and separates public-facing routes from administration with public and admin blueprints. Models cover projects, settings, and related data. Templates serve the home page, individual project details, contact page, privacy and terms pages, and a thank-you page; static assets include CSS, JavaScript, and images.

This structure supports a useful distinction: project content is stored as data, while templates determine how it is presented. Ullah says the admin dashboard is database-driven and lets him update projects, skills, certifications, and education without editing page HTML directly. Individual project pages provide a dedicated place to explain each item rather than crowding every detail onto the home page.

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Contact, privacy, and analytics

The contact form sends email through Resend. Ullah reports using Flask-WTF for CSRF protection and rate limiting to reduce unwanted submissions. These are described implementation measures, not an independent security review; they should not be read as a certification that the form or application is secure.

For analytics, the author says Google Analytics 4 loads only after cookie consent. He also reports canonical URLs, structured data for Person, FAQPage, SoftwareSourceCode, and BreadcrumbList, plus a sitemap and robots file, and says he submitted the site to Search Console. Those steps describe what he implemented; they do not establish search ranking, traffic, or legal compliance.

Reported performance and testing work

Ullah says he converted images to WebP and measured them as “50% smaller” than JPEGs. The article does not provide the image set or measurement method, so treat that as his reported result rather than a general expectation for WebP. He also says he disabled canvas particle effects on screens narrower than 768 pixels, used IntersectionObserver to trigger animations, and cache-busted CSS files.

He reports writing 27 automated pytest tests, including checks for sitemap output, robots.txt, and contact-form CSRF, and says they passed before each push. No independent test run or CI record is supplied. The number is therefore a description of the author’s test suite, not an independently verified quality or coverage measure.

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Deployment and what to take from the build

The source account says the Flask app was deployed on PythonAnywhere with a WSGI configuration. It does not establish the hosting plan, service limits, or the site’s present availability, so those details should be checked directly before using this setup for a new project. Ullah also says the GitHub repository is private, meaning the account does not offer a public codebase readers can inspect.

The most reusable idea is the content workflow: keep project information in a database, give each project its own page, and make routine portfolio updates possible through an admin interface. The exact stack makes sense for Ullah’s Python background and goals; another candidate may reasonably prioritize faster editing or fewer hosting responsibilities. As Ullah reflects, “Building this portfolio from scratch taught me more than any tutorial ever could.” That is his account of what he learned, rather than evidence that custom sites outperform tutorials or templates.

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