I’m going to explain you one of the easiest way to train YOLO to detect a custom object even if you’re a beginner and have no experience with coding. We can train YOLO to detect a custom object, I choosed for example to detect a Koala, you can choose any animal/object you prefer.

It is not a surprise that in the world of Big Data, where the use of deep neural networks (NNs) is common, processing power is essential. GPU is essential for deep learning as it can handle many small processes at the same time, which is needed to update all the weights and bias terms in the layers of deep NN. As deep NN trains, it needs to calculate, re-calculate, adjust, re-scale, and update all of the parameters in every layer of the network thousands, millions, or even billions of times. Doing all of these using CPU would lead to significant time delays. Simply, imagine updating thousand of parameters one after another.

For people who are new or still didn't use it -- Google Colab is Jupyter service with dedicated server(with GPU) that you get free for about 12 hours(after it you need to reinitialize it). So it's good place where you can test your Python scripts, or use it while you are learning Machine Learning & Data Science. First it gives free computation power and even free Nvidia Tesla K80. Don't forget to copy all intensive reading data from Drive to instance to make access faster.

In this post, I will demonstrate how to use Google Colab for fastai. Colab is a Google internal research tool for data science. They have released the tool sometime earlier to the general public with a noble goal of dissemination of machine learning education and research. Although it's been for quite a while there is a new feature that will interest a lot of people. You can use GPU as a backend for free for 12 hours at a time.

In this post, I will demonstrate how to use google colab for fastai. Google colab is a google internal research tool for data science for some time. They have released out the tool sometime earlier to the general public with a noble goal of dissemination of machine learning education and research. Although it's been for quite a while there is a new feature that will interest a lot of people. These are the kind of questions that immediately popped into my mind and I gave it a shot.