​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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