Even Oldridge
Director of Applied Research, Nemo Retriever @NVIDIA
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WORK HISTORY
Director of Applied Research, Nemo Retriever @NVIDIA
Vancouver, BC, CA
EDUCATION
The University of British Columbia
M.A.Sc., Electrical and Electronics Engineering
Fast.ai
Practical / Cutting Edge Deep Learning For Coders
The University of British Columbia
PhD, Electrical & Computer Engineering
SKILLS
ABOUT EVEN OLDRIDGE
Data Scientist with seven years of experience exploring user behaviour and metadata to discover insights, create models and generate value from petabyte scale data. ML Core Competencies:Data Cleaning, Munging, and Validation, Data Exploration, Data Analysis, Deep dive problem solving, Data Advocacy and Presentation, Feature Selection, Model Building for Classification, Regression, Clustering, and Recommendation Engines, and Model Evaluation.Deep Learning interests/experience:Deep recommender systems. Deep tabular data via embeddings and autoencoders. NLP techniques including word and sentence representations, named entity recognition, and text classification / regression. Image classification, segmentation, and similarity. Neural Art, primarily style transfer but also explorations of deep dream and GANs.Technical Skills:Deep Learning: Architecture exploration and creation, Model debugging, Hyperparameter optimization, Model regularization, Loss function tuning, Ablation studies and importance measurement.Machine Learning: Random Forest, Linear/Logistic Regression, Gradient Boosting, Support Vector Machines, Decision Trees, LSA/LDA, Bayes, PCA, Approximate Nearest Neighbors.Daily Stack: PyTorch, FastAI, Jupyter/Anaconda, AWS EC2/Athena/Glue/SagemakerHistory with: Keras, TensorFlow, BigQuery, Excel, MSSQL, RStudio
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