From the course: Full-Stack Deep Learning with Python
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Setting up the environment on Google Colab - Python Tutorial
From the course: Full-Stack Deep Learning with Python
Setting up the environment on Google Colab
- [Instructor] In this demo, we'll see how we can use MLflow to log our model parameters and metrics while we train a dense neural network to perform image classification. Now, if you're familiar with neural networks, you know that typically you would not perform image classification using dense neural networks. You use convolutional neural networks. However, here we'll start off with a dense neural network, so you know how we can use MLflow, and then we'll move on to a convolutional neural network in the next demo. Now we'll be performing our model training and even deploying MLflow on Colab. So head over to colab.research.google.com. Colab is a Google project that gives you free access to a cloud hosted Jupyter Notebook. The Colab runtime comes pre-installed with many useful Python packages that we'll use for model building and training. And most importantly, Colab allows you to access GPUs entirely free of charge, at…
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