Understanding how the dimension of your input image changes as it progresses through the Neural Network Layers can be challenging to understand at times.

There is a module named 'torchsummary' which can easily do this task for you!

Here is how it works.

A Visual Thread 🧵👇 1️⃣ Consider the above example where you have already defined a model named 'ConvNet', which has

- 2 convolutional layers,

- then a dropout

- and finally 2 linear layers.

Just secured the 1st Position 🥇 in a @kaggle community competition hosted by @weights_biases and Deep Learning Sessions Portugal!

Know more 🧵👇 The challenge was a Multiclass Image Classification Problem consisting of 8 classes of Microscopic Blood cell images.

I have written 1000s of lines of code and built multiple projects in PyTorch.

On @PyTorch 's 5 year completion, I am sharing Top 10 resources you can use to learn this awesome Deep Learning framework from scratch!

A Visual Thread (with links)🧵👇 1️⃣ PyTorch Official Tutorials -

PyTorch has some extensive and clear tutorials in all domains like Text, Audio, Image, Video, Reinforcement Learning and so on.

Link👉bit.ly/3IswPPX

I am excited to announce the registrations for Batch-7 of the Live Data Science Mentorship Session (January 2022)

400+ students across 5+ countries have taken the program & the response keeps me motivated to reach more people

Register Here - bit.ly/3FCWROp

Details 👇 There are 4 sections in the session -

1. A practical Data Science path which I followed

2. Secrets which helped me secure Top 30 ranks across multiple Machine Learning Hackathons (including Kaggle)

If you are willing to learn PyTorch and have understanding of some deep learning concepts

and hands on practice with python

then the best resource is the PyTorch Tutorials. These Tutorials are available in the orginal PyTorch Website and are complete in a sense.