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LLMs MasterClass: Last Day for Early-Bird Price
Train, Fine-Tune and Deploy Large Language Models
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Damien Benveniste
Float32 vs Float16 vs BFloat16?
Float32, Float16 or BFloat16!
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Damien Benveniste
Train, Fine-Tune, and Deploy Large Language Models Bootcamp!
Starting August 15th, 2024
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Damien Benveniste
The Position Encoding In Transformers!
Transformers and the self-attention are powerful architectures to enable large language models, but we need a mechanism for them to understand the order…
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Damien Benveniste
How To Deploy LLM Applications
Before Deploying
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Damien Benveniste
1:08:27
Introduction to Machine Learning System Design!
Machine Learning System Design is one of my favorite aspects of Machine Learning. We start with a business idea, a product ideation to deduce a whole…
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Damien Benveniste
1

June 2024

Understanding How LoRA Adapters Work!
LLM Fine-Tuning
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Damien Benveniste
1
The Backpropagation Algorithm!
Deep Learning - Neural Networks
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Damien Benveniste
1
Understanding The Computational Graph in Neural Networks
Do you know what is this computational graph used by deep learning frameworks like TensorFlow or PyTorch? The whole logic behind how neural networks…
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Damien Benveniste
Fine-Tuning LLMs: From A to Z!
The different fine-tuning tasks | LoRA | QLoRA | PEFT
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Damien Benveniste
2
1:26:40
How to Approach Model Optimization for AutoML
Since I started my career in Machine learning, I have worked hard to automate every aspect of my work. If I couldn't develop a fully production-ready…
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Damien Benveniste
Understanding CatBoost!
Catboost might be the easiest supervised learning algorithm to use today on large tabular data. It is highly parallelizable, it automatically deals with…
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Damien Benveniste
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