David Natingga

Masters in Artificial Intelligence (Imperial College London), PhD in Mathematics (University of Leeds). Ready for a big challenge in mathematics, algorithms, data science or machine learning!

Part of Toptal network of elite freelancers (only top 3% applicants are accepted): https://www.toptal.com/resume/david-natingga-phd

Machine learning

Concepts: bias-variance trade-off, recall & precision, supervised & unsupervised learning,

regularization, bagging and boosting

Deep learning: ANN, CNN (Dropout, Pool, ConvnD), architectures (VGG, AlexNet, ResNet)

Computer vision: object detection and recognition (e.g. Viola-Jones algorithm)

Statistics: least mean squares, Bayesian algorithms, regression, expectation maximization,

Markov chain, Monte Carlo method, A/B testing, hypothesis testing

Algebra: singular value decomposition

Clustering: k-means, DBSCAN, elbow method, Silhouette coefficient

Classification and regression: decision trees, random forests, gradient boosting, support vector machine,

k-nearest neighbours

Time series analysis: forecasting, trend and seasonality, burn-in, autoregressive evaluation,

dynamic time warping, anomaly detection, drift and offset detection

Online algorithms: recursive filters (e.g. Kalman filter), moving average and variance (e.g. EMA),

Welford’s algorithm

Dimensionality reduction: principal component analysis, t-Distributed Stochastic Neighbor Embedding

Bioinformatics: DNA analysis, oriC search, sequencing

Others: inductive inference, PageRank, genetic algorithms

Software engineering

Algorithms and data structures: computational and memory complexity; ADTs

Best practices: architecture, specification, code style, design patterns, documentation, review

Concepts: Agile, TDD, BDD, Scrum, MVP, CI

Version control: Git, SVN

Languages: C / C++, Java, Python, Assembly, Awk, Bash, Basic, Go, Haskell, Julia, Matlab, Pascal, Perl, Prolog, R, Ruby

Web development: CSS, HTML, JavaScript, PHP, AJAX, jQuery, CGI, sockets

Mobile development: Android

Databases: MySQL, PostgreSQL, Timescale, Berkeley DB, NoSQL, MongoDB

Networking: Apache, CISCO, Linux

Cloud computing: Amazon Web Services: EC2, S3, Batch, Lightsail

Google Cloud Platform: Storage, AI platform

Testing: unit, validation and integration testing; mock objects

Build tools: Gradle, Maven

Management software: Jenkins (DSL scripting), CircleCI, Confluence, Gerrit, Github, Zube

IDEs: Eclipse, IntelliJ IDEA, Android Studio

Additional skills: Docker containers, Nvidia CUDA, Flex, Bison, ElasticSearch, OpenAPI (Swagger)