Andres Barrera
Principal Machine Learning Curriculum Engineer at DeepLearning.AI
Bogota, Colombia
Summary
🤩
Rockstar🎓
Top SchoolAndres Barrera is a Principal Machine Learning Curriculum Engineer with nine years of experience designing and deploying ML education at scale, currently leading course development and autograding systems for DeepLearning.AI. He blends an academic foundation in Operations Research with hands-on ML engineering—building production-ready model deployments with FastAPI, Docker, TensorFlow/PyTorch, and GCP. Andres has a track record of improving learning outcomes by debugging and refactoring assignment notebooks, creating internal Python tools, and automating course delivery on Coursera. Prior roles span product-focused modeling at Delivery Hero and end-to-end ML systems at startups, where he combined vision APIs, Go, and backend services to solve real-world problems. He contributes to well-known public repos for DeepLearning.AI (including MLEP and TensorFlow exercises), showing a practical bent for turning coursework into productionized examples. Outside work he pairs a love for Go and nature with a talent for making complex concepts accessible, reflected in his tutoring and curriculum-building background.
9 years of coding experience
10 years of employment as a software developer
Universidad de los Andes
Spanish, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (15)
neural-network10
object-detection10
keras10
computer-vision10
machine-learning10
fastapi10
convolutional-neural-networks10
api10
tensorflow10
python10
machine-learning-models10
apidoc10
ml-deployment10
image-classification10
matplotlib8
Programming languages (7)
Github contributions (5)
https-deeplearning-ai/machine-learning-engineering-for-production-public
Feb 2021 - Jan 2023
Public repo for DeepLearning.AI MLEP Specialization
Role in this project:
ML Engineer
ML EngineerContributions:94 commits, 48 PRs, 70 pushes in 1 year 11 months
Contributions summary:Andres's commits primarily focus on the deployment of a machine learning model using FastAPI. The user's changes involve creating and modifying files for a server, and a client to interact with that server. These changes include setting up endpoints, and integrating the model into the API. The user also worked on image processing and object detection tasks related to the deployed model.
public-repodeeplearning-aispecializationdeep-learningmachine-learning
https-deeplearning-ai/tensorflow-1-public
Jan 2022 - Jan 2023
Role in this project:ML Engineer
ML EngineerContributions:53 commits, 43 PRs, 26 pushes in 11 months
Contributions summary:Andres added assignment notebooks for training a Convolutional Neural Network on the happy or sad dataset. The commits include code for image loading, data preprocessing, and model building with the Keras API using layers like Conv2D and Dense. The work focuses on achieving high accuracy on the image classification task.
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