Ideal for teams that…
Hands-on AI and data analytics workshops — built around your team's real cases.
How to install and configure PyTorch in your working environment
How to build, train, and optimize machine learning models with PyTorch
How to implement advanced neural networks such as CNNs and RNNs
How to prepare and deploy PyTorch models in production environments
What we actually do
- · History and development of PyTorch
- · Architecture and main components
- · Installing PyTorch and dependencies
- · Setting up the environment (Jupyter Notebook, Google Colab)
- · Operations on tensors, autograd, and computation graphs
- · Building and running simple models
- · Implementing a linear model in PyTorch
- · Training and evaluating the model on real data
- · Neural networks and their architecture
- · Implementing and training Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
- · Optimization and regularization techniques
- · Fine-tuning pretrained models in PyTorch
- · Preparing and processing image data
- · Implementing and training a CNN for image classification
- · Exporting models and preparing for deployment
- · Practical aspects of deploying models in production environments
From brief to retro in 30 days.
Brief & diagnosis
A call with the team lead + a short survey for participants. We define goals, gap and context.
Program customization
We adapt modules, case studies and code examples to your stack. Approval in 5 days.
Workshop
Trainer-led sessions, hands-on, code review. Mentor available between sessions too.
Retro + report
Outcome report for the team and lead. 30 days of consulting included.
Send a brief. We'll reply within 1 day.
After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.
Thank you!
We'll get back to you within 1 business day.
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