
4. How to Read a Machine Learning Research Paper Efficiently
In this practical work, we’ll be learning How to Read a Machine Learning Paper Efficiently.
Let’s Get Started Abstract As someone studying machine learning, you’ll have to read technical papers at several points in your life to review the current literature on specific topics you want to research. You’ve actually already come across several papers while doing the previous practical works.
Doing a literature review is essential when starting to work on a subject: People have probably already looked into the topic you want to study, so learning from their previous work will help you save time and reach a solution faster.

3. Intro to Denoising Diffusion Probabilistic Models (DDPMs) for Image Generation
In this third practical work, we’ll be experimenting with Denoising Diffusion Probabilistic Models (DDPMs).
As Usual, Get Setup Locally You should have Jupyter installed and the following dependencies. You can use pip or any other dependency manager:
pip install torch einops datasets matplotlib tqdm You can add more dependencies if you think it is relevant.
In The Cloud (Google Colab) Simply click here to open a Colab notebook in your browser.

2. Intro to Convolutional Neural Networks (CNNs) in PyTorch
In this second practical work, we’ll be experimenting with Convolutional Neural Networks (CNNs).
As Usual, Get Setup Locally You should have Jupyter installed and the following dependencies. You can use pip or any other dependency manager:
pip install torch torchvision matplotlib scikit-learn You can add more dependencies if you think it is relevant.
In The Cloud (Google Colab) Simply click here to open a Colab notebook in your browser. You’ll need to sign-in with you Google account.

1. Build a Neural Network in PyTorch
In this first practical work, we’ll be experimenting with simple neural networks on simple datasets.
First, Get Setup It’s recommended to use a Jupyter notebook since you’ll be doing some visualization.
Locally You should have Jupyter installed and the following dependencies. You can use pip or any other dependency manager:
pip install torch matplotlib scikit-learn You can add more dependencies if you think it is relevant.
In The Cloud (Google Colab) Simply click here to open a Colab notebook in your browser.