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In this article, you will learn how to build python-based gesture-controlled applications using AI. We will guide you all the way with step-by-step instructions. I’m sure you will have loads
In this post, we continue to consider how to speed up inference quickly and painlessly if we already have a trained model in PyTorch. In the previous post We discussed
A picture is worth a thousand words! As computer vision and machine learning experts, we could not agree more. Human intuition is the most powerful way of making sense out
At LearnOpenCV.com, we have adopted a mission of helping people take their first steps in the fields of Machine Learning, Computer Vision, Deep Learning, and AI. We have created a
Neural network usage usually takes a lot of computations, but in our modern world, even a smartphone can be a device to run your trained neural model. Today we will
Let’s play rock, paper scissors. You think of your move and I’ll make mine below this line in 1…2…and 3. I choose ROCK. Well? …who won. It doesn’t matter cause
The life of a machine learning engineer consists of long stretches of frustration and a few moments of joy! First, struggle to get your model to produce good results on
In an earlier post, we covered the problem of Multi Label Image Classification (MLIC) for Image Tagging. Recall that MLIC is an image classification task but unlike multi-class image classification
This is a a gentle introduction to federated learning — a technique that makes machine learning more secure by training on decentralized data. We will also cover a real-life example
Wouldn’t it be cool if you could just wave a pen in the air to draw something virtually and it actually draws it on the screen? It could be even
Imagine, one day you have an amazing idea for your machine learning project. You write down all the details on a piece of paper- the model architecture, the optimizer, the
In the previous post, we learned how to apply a fixed number of tags to images. Let’s now switch to this broader task and see how we can tackle it.
