Aurélien Géron
ML Book Author at Self-Employed
Auckland, Auckland, New Zealand
Summary
🤩
Rockstar🎓
Top SchoolAurélien Géron is a machine learning engineer, author and entrepreneur with over 17 years of software and AI experience, best known for the #1 Amazon best-selling "Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow." He blends deep technical contributions to flagship open-source projects—Keras, TensorFlow, scikit-learn and TF Datasets—with practical teaching through notebooks, courses and workshop labs. A former YouTube product manager and founder/CTO of multiple startups, he moves comfortably between product, research and hands-on engineering. His open-source work ranges from improving core ML libraries (Gaussian Mixtures, MultiHeadAttention masking) to user-facing front-end tweaks for the Abstraction and Reasoning Corpus, showing both low-level rigor and UX sensibility. Based in Auckland and recognized as a Google Developer Expert, he continuously updates educational material to track major API shifts like TensorFlow 2.0. Beyond books, he quietly maintains rich tutorial repositories (including a capsule network notebook) that power real-world learning and adoption.
17 years of coding experience
21 years of employment as a software developer
Master of Engineering - MEng, Computer Science, Master of Engineering - MEng, Computer Science at AgroParisTech - Institut des sciences et industries du vivant et de l'environnement
French, English, Spanish
Github Skills (40)
javascript10
pytest10
python10
machine-learning-models10
data-science10
data-set10
scikit10
tfx10
css10
machine-learning10
rnn-model10
n10
reinforcement-learning10
data-model10
datasets10
Programming languages (18)
Github contributions (5)
ageron/handson-ml3
Feb 2016 - Oct 2022
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Role in this project:
ML Engineer
ML EngineerContributions:881 commits, 23 PRs, 118 pushes in 6 years 9 months
Contributions summary:Aurélien appears to be primarily involved in developing and adding new machine learning models or functionality to the repository. This is evident from their commits, which include the addition of a capsule network notebook. Their contributions seem focused on the application of machine learning, as demonstrated by their edits to existing project code, such as the end-to-end machine learning project notebook.
deep-learningjupyter-notebookkerasmachine-learningpython
ageron/tf2_course
Jan 2019 - Jun 2022
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
Role in this project:ML Engineer
ML EngineerContributions:66 commits, 13 PRs, 45 pushes in 3 years 6 months
Contributions summary:Aurélien's commits focus on developing and implementing neural networks using the Keras API within the TensorFlow 2 framework. They introduced and modified notebooks for a "Deep Learning with TensorFlow 2 and Keras" course. Their contributions include initial notebook versions, the introduction of loss functions, metrics, optimizers, and the addition of examples using tf.function, graphs and autodiff. They also implemented a CNN and a deep net architecture.
deep-learningkerastensorflow
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