Ray A Framework for Scaling and Distributing Python & ML Applications | Anyscale
Modern machine learning (ML) workloads, such as deep learning and large-scale model training, are compute-intensive and require distributed execution. Ray is an open-source, distributed framework from U.C. Berkeley’s RISELab that easily scales Python applications and ML workloads from a laptop to a cluster, with an emphasis on the unique performance challenges of ML/AI systems. It […]
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How to Scale up your Pandas workflows with Modin
pandas is one of the most commonly used data science libraries in Python, with a convenient set of APIs to help data scientists prepare, analyze, and explore their data. However, despite its widespread adoption, pandas suffers from severe memory and performance issues on moderately large datasets. This presentation focuses on Modin, a fast, scalable drop-in […]
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The Modern Stack for ML Infrastructure
Metaflow was originally developed at Netflix to provide a user-friendly platform for a wide range of ML use cases from computer vision and NLP to classical statistics. Today, Metaflow is used by hundreds of companies from real estate and finance to biotech and drones. In this talk, we give a technical overview of Metaflow, showing […]
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YOLOX + DEEPSORT | Multi-Object Detection with Dynamic Thickness and Corners B-Boxes
Computer vision and object detection is getting easier and easier.
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YOLOR + Vehicle Detection and Hiding Them
With YOLOR you can create almost anything and your imagination is the limit.
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OpenCV Python Tutorial #3 | Reading an Image
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Frank
- February 14, 2022
- artificial intelligence
- Computer Vision
- computer vision algorithms
- computer vision tutorial
- computer vision tutorials
- image processing
- OpenCV
- opencv python
- opencv python tutorial
- opencv tutorial
- opencv tutorials
- python course
- python for beginners
- python tutorial for beginners
- TensorFlow
In lesson 3 of the OpenCV Course you will learn how to Read in a simple Image which we will then use for processing using the OpenCV Library.
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Street Signs and Object Detection
I had a discussion recently about the state of the art in computer vision and whether or not AI could read street signs in real time. A project implemented by Karol Majek that can detect multiple objects in the street – light post, manholes🕳️, street signs and lights🚦 and more. Special Thanks to Karol Majek […]
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OpenCV Python Tutorial #1 | Introduction
In this tutorial you will learn what is OpenCV and its myriad of applications.
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PyTorch and Monai for AI Healthcare Imaging – Python Machine Learning Course
Learn how to use PyTorch, Monai, and Python for computer vision using machine learning. One practical use-case for artificial intelligence is healthcare imaging. In this course, you will improve your machine learning skills by creating an algorithm for automatic liver segmentation. Code: https://github.com/amine0110/Liver-Segmentation-Using-Monai-and-PyTorch Course Contents: (0:00:00) Introduction (0:02:11) What is U-Net (0:13:21) Software Installation (0:22:35) […]
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Fourier Feature Networks and Neural Volume Rendering
Fourier Feature Networks are an exciting new development in Computer Vision, and their use for modeling radiance fields has produced a range of impressive results at the meeting point of Computer Vision and Computer Graphics. In this lecture, Matthew covers the motivation behind using Fourier features in neural network training, introduces the fundamentals of volumetric […]
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