Preplp
Build & Deploy ML Apps

1. Introduction

6 minStep 1 of 16

Build a Flask OCR app — upload an image, extract text with Tesseract, display results in the browser

What you'll need

  • Python 3.8–3.10 recommended. You need Tesseract installed system-wide, plus pip packages below.
  • Tesseract OCR installed on your machine (brew install tesseract on Mac, apt install tesseract-ocr on Linux)

Why this matters

OCR powers receipt scanning, document digitization, and ID verification pipelines. You practice the same upload → preprocess → ML library → display loop as production document AI apps.

What you'll have at the end

A local Flask site where you upload a photo with text, click Extract, and see each line of recognized text beside the image. Portfolio-ready Python full-stack work.

FlaskpytesseractOpenCVgrayscalefile upload
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One rehearsal platform

Certification mocks, daily lessons, project labs, and in-browser drills

Structured for exam day and portfolio proof — timed tests, guided builds, and quick reps on one platform.