UI for a Search API with Flask and Bootstrap

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prerequisites
intermediate Python • basic Docker • manipulations with tuples, lists and dictionaries
skills learned
packaging and deploying with Docker • search and indexing with Elasticsearch • building APIs with Flask
Olesya Bondarenko
1 week · 9-15 hours per week · INTERMEDIATE
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Look inside
In this liveProject, you’ll use Docker, the Docker compose command line, and Bootstrap to construct an easy-to-use UI for your search engine. You’ll work to set up a single node Elasticsearch cluster, before putting together your Bootstrap UI, and then create a customized Docker image of the Flask API that serves your transformers model and frontend.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Olesya Bondarenko
Olesya Bondarenko has a multidisciplinary background and experience in natural language processing (NLP), machine learning, deep learning, statistics, time-series analysis, process automation, engineering R&D and new product prototyping. Currently, she is a data scientist at Strong Analytics, a leading provider of customized AI solutions, where she specializes in developing NLP systems. Prior to joining Strong, she worked with several startups leading research and development efforts in the areas of conversational AI, data-leveraged scientific discovery solutions, and a variety of automated analytic and data collection tools. Olesya received her PhD in electrical engineering from the University of California San Diego where she designed and prototyped novel optical devices, as well as custom instrumentation for their analysis.

prerequisites

This liveProject is for intermediate Python programmers familiar with the command line and Docker. To begin this liveProject you will need to be familiar with:

TOOLS
  • Intermediate Python
  • Basic understanding of CLIs
  • Basic Elasticsearch
  • Basic HTML
  • Basic Docker
  • Basic Flask web development
TECHNIQUES
  • Reading data from and writing to JSON files
  • Manipulations with tuples, lists, and dictionaries using loops and comprehensions

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