Deep Learning with PyTorch
Details
Image Classification with PyTorch: ML Zoomcamp Module Update - Alexey Grigorev
This is the fourth workshop in our ML series on ML model deployment and engineering.
In the ML Zoomcamp course, our Deep Learning module has traditionally focused on TensorFlow and Keras. But PyTorch has rapidly become the dominant framework for deep learning.
In this workshop, we’ll demonstrate how to implement key concepts, like convolutional neural networks, transfer learning, and training loops, using PyTorch.
Led by Alexey Grigorev, this hands-on workshop demonstrates how to rewrite a TensorFlow/Keras project into PyTorch and train image classifiers.
What you’ll learn:
- How to set up a deep learning project in PyTorch
- How to implement convolutional neural networks (CNNs) from scratch
- How to apply transfer learning with pre-trained models like MobileNet
- Key differences between TensorFlow/Keras and PyTorch
- How to handle data preprocessing and augmentation in PyTorch
- How to evaluate, checkpoint, and improve your models
By the end, you’ll have a working PyTorch training pipeline and an understanding of how it maps to the TensorFlow/Keras version.
Like the other workshops, this will be a live demo with practical tips and time for Q&A.
Thinking About ML Zoomcamp?
This workshop reflects the updated Deep Learning module (Module 8) in the ML Zoomcamp. You’ll get a preview of how the course now includes both TensorFlow and PyTorch, so you can choose the framework that fits your workflow.
ML Zoomcamp is our free 4-month course that takes you from beginner to advanced ML engineer. It covers the fundamentals of ML, from regression and classification to deployment and deep learning.
The new cohort of the ML Zoomcamp starts on September 15, 2025. You can join it by registering here.
About the Speaker
Alexey Grigorev is the Founder of DataTalks.Club and creator of the Zoomcamp series.
Alexey is a seasoned software and ML engineer with over 10 years in engineering and 6+ years in machine learning. He has deployed large-scale ML systems at companies like OLX Group and Simplaex, authored several technical books including Machine Learning Bookcamp, and is a Kaggle Master with a 1st place finish in the NIPS'17 Criteo Challenge.
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Deep Learning with PyTorch