Daniel Bourke

Greater Brisbane Area Australia

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Summary

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Rockstar

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Top School

Daniel Bourke is a machine learning engineer and technical content creator with a decade of experience building open-source AI and on-device computer vision for health applications. He leads ML education at Zero To Mastery, creates widely used TensorFlow and PyTorch course materials, and produces hands-on tutorials and benchmarks (including M1 TensorFlow benchmarking notebooks) that make complex topics approachable. At Nutrify he develops real-time models that identify 1000+ foods on-device, while at Artificial Analysis he benchmarks state-of-the-art AI models and turns results into clear technical media. Combining a BSc in Food Science & Nutrition with deep learning credentials and a history of public teaching via YouTube, he uniquely blends domain knowledge in health with practical ML engineering. Known for turning personal interests into focused projects, he builds fast prototypes, talks confidently to diverse audiences, and open-sources his teaching materials for global impact.

10 years of coding experience

2 years of employment as a software developer

Specialisation, Deep Learning, Specialisation, Deep Learning at Coursera

Nanodegree, Artificial Intelligence, Nanodegree, Artificial Intelligence at Udacity

St. Patrick's College, Shorncliffe

Certificate in New Ventures Leadership, MIT Global Entrepreneurship Bootcamp, Certificate in New Ventures Leadership, MIT Global Entrepreneurship Bootcamp at Massachusetts Institute of Technology

Bachelor of Science (BSc), Food Science and Nutrition, Bachelor of Science (BSc), Food Science and Nutrition at The University of Queensland

Machine Learning, Coursera, Machine Learning, Coursera at Stanford University

Stackoverflow

Stats

406reputation

55kreached

5answers

13questions

Github Skills (22)

pytorch10

cifar10010

python10

evaluation10

machine-learning-models10

data-science10

machine-learning10

gcp10

eval10

deep-learning10

tensorflow10

computer-vision10

jupyter-notebook10

streamlit10

benchmark9

Programming languages (6)

TypeScriptShellC++HTMLJupyter NotebookPython

Github contributions (5)

mrdbourke/cs329s-ml-deployment-tutorial

Feb 2021 - Feb 2021

Code and files to go along with CS329s machine learning model deployment tutorial.

Role in this project:

ML Engineer

Contributions:43 commits, 33 pushes, 1 branch in 13 days

Contributions summary:Daniel's commits primarily involve the development of a Streamlit application for deploying a food vision machine learning model. They implemented the application logic, including image loading, model prediction, and a feedback mechanism. The user also worked on integrating a TensorFlow model and interacting with Google Cloud Platform (GCP) services.

cloud-servicespythonmachine-learning-tutorialapp-enginedeployment

mrdbourke/tensorflow-deep-learning

Nov 2020 - Sep 2022

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Role in this project:

Data Scientist & ML Engineer

Contributions:1 review, 503 commits, 32 PRs in 1 year 10 months

Contributions summary:Daniel's primary contribution to the project appears to be in building the foundational elements of a deep learning project using TensorFlow. The user implemented the initial structure of a notebook focused on the basics of TensorFlow, covering creating tensors, extracting tensor information, and manipulating tensors. This focus on the fundamentals of deep learning, along with the specific use of the TensorFlow library indicates a Data Scientist and ML Engineer role.

curriculummxnetzerodeep-learningdeep-neural-networks

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