GIFs Search Engine and Performance Optimization Project

The high-level goal of this project is oriented towards improving a search engine to better understand the user’s intent behind the search query and suggest the matching imagery. To achieve this goal, our team has designed, built, validated and trained an API that encompasses several Machine Learning algorithms.

  • Deep Convolutional Neural Networks (ConvNet or CNN
  • Deep Recurrent Neural Networks
  • Reinforcement Learning
  • Continuous Learning
  • Metric Learning
  • Sequence to Sequence Architecture
  • Word2Vec
  • Word Embeddings
  • Word Lemmatization and Tokenization
  • Faces Embedding
  • Infrastructure as Code (IaC)
  • Keras
  • PyTorch
  • Kubernetes
  • AWS S3
  • Docker
  • CI/CD
  • Terraform
  • TensorFlow
  • Jenkins
  • Redshift
  • Python
  • Babel
  • React
  • NewRelic
  • Django
  • Gunicorn
  • WebPack
  • Scala
  • Protobuf
  • Spark
  • Akka
  • Akka HTTP
  • Akka Streams

Fill out the form below to download the full case study

    GIFs Search Engine and Performance Optimization Project

    Stand with Ukraine

    We stand with our friends and colleagues during this struggle for their freedom and independence—and lives, above all. To support Ukraine in its direst hours, visit this page.