Jovian.ml Hub
Jovian.ml is a sharing and collaboration platform for data science projects. This post is a follow-up the introductory post on sharing & embedding Jupyter notebooks online with Jovian. Jupyter notebooks are great for interactive programming and visualization of outputs. For this very reason, however, it is sometimes quite difficult to version control Jupyter notebooks. Git […]
Part 4 of “PyTorch: Zero to GANs” This post is the fourth in a series of tutorials on building deep learning models with PyTorch, an open source neural networks library. Check out the full series: PyTorch Basics: Tensors & Gradients Linear Regression & Gradient Descent Classification using Logistic Regression Feedforward Neural Networks & Training on GPUs […]
Build a state-of-the-art movie recommendation system with just 10 lines of code Recommender systems are at the core of pretty much every online service we interact with. Social networking sites like Facebook, Twitter and Instagram recommend posts you might like, or people you might know. Video streaming services like YouTube and Netflix recommend videos, movies […]
Part 3 of “PyTorch: Zero to GANs” This post is the third in a series of tutorials on building deep learning models with PyTorch, an open source neural networks library. Check out the full series: PyTorch Basics: Tensors & Gradients Linear Regression & Gradient Descent Classification using Logistic Regression (this post) Feedforward Neural Networks & Training […]
Part 2 of “PyTorch: Zero to GANs” This post is the second in a series of tutorials on building deep learning models with PyTorch, an open source neural networks library developed and maintained by Facebook. Check out the full series: PyTorch Basics: Tensors & Gradients Linear Regression & Gradient Descent (this post) Classification using Logistic Regression […]
Part 1 of “PyTorch: Zero to GANs” This post is the first in a series of tutorials on building deep learning models with PyTorch, an open source neural networks library developed and maintained by Facebook. Check out the full series: PyTorch Basics: Tensors & Gradients (this post) Linear Regression & Gradient Descent Classification using Logistic […]
Using PyTorch, FastAI and the CIFAR-10 image dataset In this article, we’ll try to replicate the approach used by the FastAI team to win the Stanford DAWNBench competition by training a model that achieves 94% accuracy on the CIFAR-10 dataset in under 3 minutes. NOTE: Some basic familiarity with PyTorch and the FastAI library is […]