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computer vision

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Building a Machine Learning Platform [Definitive Guide]

Stephen Oladele, 10 min
Moving across the typical machine learning lifecycle can be a nightmare. From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot.  As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers…
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Object Detection with YOLO: Hands-on Tutorial

by Anton Morgunov, 10 min read
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Building MLOps Pipeline for Computer Vision: Image Classification Task [Tutorial]

by Nilesh Barla, 18 min read
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Imbalanced Data in Object Detection Computer Vision Projects

by Tanay Agrawal, 9 min read
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Deploying Computer Vision Models: Tools & Best Practices

by Arun C John, 25 min read
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Self-Supervised Learning and Its Applications

by Deval Shah, Abhishek Jha, 12 min read
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Pix2pix: Key Model Architecture Decisions

by Nilesh Barla, 13 min read
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Deploying Your Next Image Classification on Serverless (AWS Lambda, GCP Cloud Function, Azure Automation)

by Stephen Oladele, 22 min read
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Training and Debugging Deep Convolutional Generative Adversarial Networks

by Aymane Hachcham, 9 min read
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Object Detection Algorithms and Libraries

by Bharath K, 13 min read
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Self-Driving Cars With Convolutional Neural Networks (CNN)

by Nilesh Barla, 12 min read
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15 Computer Visions Projects You Can Do Right Now

by Harshil Patel, 11 min read
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How to Choose a Loss Function For Face Recognition

by Charudatta Manwatkar, 11 min read
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