The AI Guy
Data Science Lead
London, England, United Kingdom
Summary
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RockstarThe AI Guy is a Data Science Lead at a major UK fintech with six years’ experience building production ML systems and mentoring teams to adopt data-driven cultures. Based in London, he combines hands-on computer vision engineering—contributing open-source YOLOv3/4 and DeepSort integrations, GPU-enabled APIs, and license-plate OCR plumbing—with strategic coaching on career transitions from analyst to data scientist. He publishes practical tutorials and teaches the often-overlooked career skills required to build and scale data science capability inside organisations. Comfortable shipping models, APIs, and Colab-friendly workflows, he bridges research, implementation, and organizational adoption to turn ML prototypes into repeatable products.
6 years of coding experience
Github Skills (20)
object-tracking10
python10
tensorflow10
object-detection10
computer-vision10
yolov410
tess4j9
image-processing9
integrate9
integrations9
machine-learning9
ocr9
tesseract9
tesseractjs9
deep-learning9
Programming languages (1)
Github contributions (5)
theAIGuysCode/Object-Detection-API
Feb 2020 - Sep 2020
Yolov3 Object Detection implemented as APIs, using TensorFlow and Flask
Role in this project:
ML Engineer
ML EngineerContributions:58 commits, 2 PRs, 57 pushes in 7 months
Contributions summary:The primarily focused on the implementation and modification of a YOLOv3 object detection API. Their contributions included adding and modifying files related to the model, including the `models.py` file with model definitions and the `detect_video.py` file which implemented object detection on videos. Additionally, the user updated models to function with a GPU and added features such as displaying FPS.
deep-learningflaskinferenceobject-detectiontensorflow
theAIGuysCode/yolov4-custom-functions
Aug 2020 - Oct 2020
A Wide Range of Custom Functions for YOLOv4, YOLOv4-tiny, YOLOv3, and YOLOv3-tiny Implemented in TensorFlow, TFLite, and TensorRT.
Role in this project:ML Engineer
ML EngineerContributions:43 commits, 42 pushes, 1 branch in 2 months
Contributions summary:The primarily contributed to the implementation and enhancement of object detection functionalities within the YOLOv4 framework. Their work involved modifying existing code for detection, including updating parameters, adding features to crop and save detections from images, and implementing a class filtering mechanism. They also integrated Tesseract OCR for license plate recognition. These contributions demonstrate a focus on extending the capabilities of the object detection models and expanding their applicability.
custom-yolov4yolov4-tinytinyobject-detectioncustom-functions
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