Using gpus in Pytorch
In the upcoming series of blog posts, we will look into how to use multiple gpus with Pytorch. Ultimately our aim is to get used to DataParallel and DistributedDataParallel models of pytorch. These abstracts allow us to use multiple gpus for inference and training with minimal code changes. There are many advantages of using multiple gpus. […]
Continue ReadingWho’s Who of Deep Learning Eco-System
Alexnet, which started the deep learning revolution, was loosely based on a network architecture(LENet) proposed by Yann Lecun in 1998. However, back then, we didn’t have the compute or the training data to train and produce the results like Alexnet. Alex used Nvidia GPUs for training, in fact he used two GPUs to train which […]
Continue ReadingIntro to AI and Machine Learning for Technical Managers
In 2013, Google acquired a company called DeepMind for 400 Million dollars. DeepMind at the time had no product and no revenue, but what they had was a team of the best brains in the world who worked on Machine learning and Deep Learning. In fact, between 2013 and 2015, all the technology giants(Facebook, […]
Continue ReadingHuman pose estimation using Deep Learning in OpenCV
I recently came across a very interesting use-case of computer vision and AI. Runners Need is a UK based sports shoe brand. They offer automated gait analysis using computer vision before they sell you a customized shoe. Gait analysis is a method for identifying biomechanical abnormalities in the way in which you walk or run. A video […]
Continue ReadingIntroduction to Generative Adversarial Network
Artificial Intelligence has improved quite a lot in the last decade. By improvement I mean we’re able to do things better than before as well as we can now do things that we didn’t even imagine, but now we and machines both can imagine. What ! machines can imagine ? Yes you heard it right ! […]
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