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Developing Large Language Models

Start your journey to developing Large Language Models (LLMs) today! In this track, you'll learn about the latest techniques for developing state-of-the-art language models responsible for the recent boom in generative AI models, like OpenAI's GPT-4, Meta's LLaMA 2, Mistral-7B, and Anthropic's Claude. Master deep learning with PyTorch to discover how neural networks can be used to model patterns in unstructured data, such as text. Discover how the transformer architecture has revolutionized text modeling, and build your own transformer model from scratch! Finally, learn to work with and fine-tune pre-trained LLMs available from Hugging Face.

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1
Python
Introduction to Deep Learning with PyTorch

Learn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch.

4 hours

Maham Khan Headshot

Maham Khan

Senior Data Scientist, YouView TV

2
Python
Intermediate Deep Learning with PyTorch

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

4 hours

Michał Oleszak Headshot

Michał Oleszak

Machine Learning Engineer

3
Python
Deep Learning for Text with PyTorch

Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

4 hours

Shubham Jain Headshot

Shubham Jain

Data Scientist

4
Python
Introduction to LLMs in Python

Learn the nuts and bolts of LLMs and the revolutionary transformer architecture they are based on!

4 hours

Iván P.C. Headshot

Iván P.C.

Senior Data Science & AI Manager

5
Python
Analyzing Car Reviews with LLMs

Use LLMs to solve diverse language tasks for a car dealership company.

2 hours

6

code-along

Fine-Tuning Your Own Llama 2 Model

In this session, we take a step-by-step approach to fine-tune a Llama 2 model on a custom dataset.

7

blog

LLMOps Essentials: A Practical Guide to Operationalizing Large Language Models

Explore the essentials of LLMOps with our guide on operationalizing Large Language Models for efficiency and reliability in AI applications.

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Instructors

  • Maham Khan Headshot
    Maham KhanSenior Data Scientist, YouView TVSee Maham Khan's Portfolio
  • Thomas Hossler Headshot
    Thomas HosslerSenior Machine Learning EngineerSee Thomas Hossler's Portfolio
  • Michał Oleszak Headshot
    Michał OleszakMachine Learning EngineerSee Michał Oleszak's Portfolio
  • Shubham Jain Headshot
    Shubham JainData ScientistSee Shubham Jain's Portfolio

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