Home web music centre

Mentors: Dan Homorodean, Marius Adam, Andra Barsoianu
Description: Web application aimed at being used in a local area network for storage, search and playback of own music gallery. The application exposes a web interface accessible from the devices in the local network with advanced search capabilities and music playback feature. The app allows music media file upload and performs analysis and advanced search on the indexed media files.
Features:

• Music file format supported: mp3
• Files metadata used in providing the search features:
  • Song lyrics – through lyrics download from 3rd party web services
  • Mp3 file ID3 tags – see https://en.wikipedia.org/wiki/ID3 – through use of 3rd party libraries
  • File name and size – name and artist extraction through patterns, classification by file size
• The mp3s will be analysed and their features will be extracted, processed, and indexed into Elasticsearch. Potentially, external APIs will be called to enrich the data obtained in this step (e.g. with lyrics, additional information about the songs and artists, etc.)
• The user will be able to search his/her music library for songs that match a specific keyword (e.g. a mood, which can be determined based on the song?€?s BPM). S/he will also be able to filter and sort the retrieved result set.

Categories: web programming, object-oriented programming, search engines, REST services, media formats, mp3
Technologies: PHP, Elasticsearch
Positions: 2

Use PredictionIO to boost Magento sales

Mentors: Bogdan Costea, Marian Mates
Description: Apache PredictionIO is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task.

During the mentorship, you will develop a Magento module that makes use of PredictionIO’s recommendation engine to make predictions about what a user is really going to buy, or what a user may like or dislike.

Technologies: PHP7.2, MySQL, Docker, RESTful API, Magento 1
Positions: 1

Launcher

Tutors: Claudiu Nicola, Calin Pristavu
Description: Web platform to facilitate communication between companies and students in order to conduct the internships. The platform will allow companies to make visible their offerings for each. The students will be able to view all offers available for their domains and apply directly through the platform.
Technologies: PHP, MySQL, JavaScript, HTML, CSS
Positions: 1

Simply send your CV at georgiana.bofan@evozon.com until 14.02.2019 and specify the project idea in which you are interested and we’ll take it from there!