Julien Bélanger

Julien Bélanger Machine Learning Developer- Summary I look forward to great advances in Artificial Intelligence and aspire to throw light on some parcels myself. I've gathered skills in the domain and I'm looking toward new struggles to put those abilities at test. I've completed a Udacity Nanodegree in Machine Learning and experienced Physics and Mathematics at University of Montreal. I'm familiar with widely used AI standards such as Support Vector Machines, Feature Extraction Clustering and Principal Component Analysis altogether with state of the art algorithms such as Recurrent Neural Networks, Encoder/Decoder Architectures and Convolutional Unets. I've laid my hands on development environments including Amazon Web Service EC2 multi-GPU machines and Google Compute Engine. I'm familiar to TensorFlow, Keras and Scikit-Learn and plan on trying the dynamic PyTorch libraries. I'm fluent in both Python and JavaScript and have some grasp on Java. Experience Enabling Machine Learning in Corporate Training September 2017 - Present Artificial Intelligence Tutorials Series June 2017 - September 2017 (4 months) I've built a serie of Artificial Intelligence tutorials for an educator. Each were displayed using Jupyter-Notebooks (interactive Python-HTML framework) and walked the readers from the very basis of AI to good-knowledge of theory and implementation using libraries such as TensorFlow and Keras. Using Machine Learning to rewrite Legacy Software Proof of Concept January 2017 - March 2017 (3 months) I lead a proof of concept exploring how to leverage machine learning to rewrite a legacy in-house engineering software for a large manufacturer. To tackle the specific challenges of the client, we designed a LSTM neural network architecture. Page 1 The POC proved the machine learning model had a good learning rate even with limited data. These results lead the client to prioritize machine learning as the architecture to replace its legacy application for a fraction of initially planned costs and delays. Technologies used: Keras, TensorFlow, Python, multi-GPU enabled AWS EC2 servers. Education Udacity Nanodegree, Machine Learning, 2016 - 2016 Activities and Societies: Forum Discussions, Paired-Coding Help Strata+Hadoop World Conference 2017 Attenders, Data Science, Big Data and Business Fundamentals, 2017 - 2017 Université de Montréal Theoretical and Computational Physics, 2015 - 2016 Activities and Societies: Student Choir, Student Cafe Cégep de St-Laurent Pure and Applied Science DEC, 2012 - 2014 Activities and Societies: Student Radio, Student Event Organisation Udacity Computability, Complexity & Algorithms, 2017 - 2017 Page 2 Julien Bélanger Machine Learning Developer- Contact Julien on LinkedIn Page 3