David Silver

California, United States

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Summary

🤩

Rockstar

David Silver is a Staff Software Engineer at Kodiak Robotics with 13 years of experience building planning, control, simulation, and mapping software for self-driving trucks. He previously accelerated motion planning and vehicle controls at Cruise (and Voyage) and evaluated domain controllers, vision, and localization at Ford, giving him deep systems and vehicle-level expertise. He led Udacity’s self-driving cars curriculum and contributed to popular CarND TensorFlow labs (including a LeNet implementation), demonstrating a blend of practical ML knowledge and pedagogy. David also founded and bootstrapped Candidate Metrics, which was acquired by HireVue, so he brings founder-level product and business experience alongside engineering. Based in California and holding a BSE in Computer Science from Princeton and an MBA from Stanford GSB, he writes about self-driving cars and uniquely combines hands-on technical work with curriculum design and startup instincts.

13 years of coding experience

Github Skills (14)

neural-network10

convolutional-neural-network10

tensorflow210

machine-learning10

neuralnetwork10

jupyter-notebook10

convolutional-neural-networks10

tensorflow10

neural-networks10

python10

mnist10

data-science10

deep-learning9

computer-vision8

Programming languages (6)

JavaC++CMakeJupyter NotebookRubyPython

Github contributions (5)

udacity/CarND-LeNet-Lab

Dec 2016 - Jan 2017

Implement the LeNet deep neural network model with TensorFlow.

Role in this project:

ML Engineer

Contributions:31 commits, 2 PRs, 19 pushes in 19 days

Contributions summary:David's primary contribution involves the implementation of a LeNet deep neural network model using TensorFlow within the specified repository. The commits showcase the creation of the LeNet lab solution, including the architecture definition and training pipeline. The user's work focuses on defining the network layers, activation functions, and training the model on the MNIST dataset. Further commits include hyperparameter tuning and improvements to the solution notebook.

lenetdeep-learningdeep-neural-networkneural-networktensorflow

udacity/CarND-TensorFlow-Lab

Nov 2016 - Dec 2016

TensorFlow Lab for Self-Driving Car ND

Role in this project:

Data Scientist

Contributions:8 commits, 3 PRs, 2 pushes in 16 days

Contributions summary:David primarily contributed to the TensorFlow Lab, focusing on improving the existing code and documentation. Their commits included fixing typos, improving explanations related to Min-Max scaling, and updating the TensorFlow Variable initialization function. Furthermore, the user focused on modifying the notebook, specifically in areas involving the neural network training.

vehicle-detectiondeep-learningself-drivingmachine-learningtensorflow

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