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Eliot Andres

Eliot Andres

Paris, France
Member since June 6, 2018
Eliot is a capable young engineer specializing in machine learning and deep learning. He helps his clients create functional prototypes and optimize existing models. With a solid academic foundation and a couple years of professional experience under his belt, he is sure to be an asset to any project.
Eliot is now available for hire
Portfolio
Experience
  • Scikit-learn, 3 years
  • Python 3, 3 years
  • Computer Vision, 2 years
  • Keras, 2 years
  • TensorFlow, 2 years
  • XGBoost, 2 years
  • iOS, 2 years
  • MLKit, 1 year
Paris, France
Availability
Part-time
Preferred Environment
Linux, Git, Python
The most amazing...
...project I've contributed to involved processing 100+ million images/month with deep learning.
Employment
  • Freelance Machine Learning Engineer
    2017 - PRESENT
    Freelance
    • Developed face emotion detection, retraining face landmarks and migrating to iOS.
    • Ported models (SVM, CNN) to CoreML on iOS.
    • Made sales predictions using XGBoost for a national bank.
    • Developed retinopathy detection using convolutional neural networks.
    • Built quality insurance on a production line on Android devices using deep learning.
    • Developed real-time semantic image search using word vectors and CNNs.
    Technologies: Tensorflow, Scikit-Learn, Dlib, XGBoost, Core ML
  • Deep Learning Engineer
    2017 - 2017
    Linkfluence
    • Developed a logo detection algorithm using the latest deep learning architectures (Bi-LSTM, CNN, attention networks).
    • Set up the infrastructure to apply this algorithm in production. Performance: 100+ million images per month.
    Technologies: Tensorflow, Keras, Kafka
  • Back-end Engineer
    2016 - 2016
    Mbr Targeting
    • Enhanced the Node.js stack, handling more than 25 billion queries/month.
    • Made extensive use of Redis, Kafka, ZeroMQ, and Aerospike.
    • Implemented Node profiling and monitoring.
    • Improved deployment procedure using Puppet, Nagios, and Cyanite.
    Technologies: Kafka, Node.js, Aerospike, Impala
Experience
  • Pretrained.ml (Development)
    http://pretrained.ml/

    List of deep learning models with demos.

  • List of Solutions to ML Problems (Development)
    http://ndres.me/kaggle-past-solutions/

    A sortable and searchable compilation of solutions to past Kaggle competitions.

    If you are facing a data science problem, there is a good chance that you can find inspiration here.

Skills
  • Languages
    Python 3, JavaScript 6
  • Frameworks
    Core ML, MLKit
  • Libraries/APIs
    TensorFlow, Keras, XGBoost, Scikit-learn
  • Paradigms
    Agile
  • Platforms
    iOS, Android
  • Other
    Computer Vision, Computer Vision Algorithms
Education
  • Master's degree in Computer Engineering
    2013 - 2017
    Ecole des Ponts et Chaussées - Paris
Certifications
  • Structuring Machine Learning Projects
    AUGUST 2017 - PRESENT
    Coursera
  • Neural Networks and Deep Learning
    AUGUST 2017 - PRESENT
    Coursera
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