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Technical Breakdowns

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Neural Networks

Dive into exactly how they work. No prior knowledge required!

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Retrieval Augmented Generation (RAG)

An alternative to fine tuning. Let's give LLMs access to a database!

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Intro to RL - Part 2

Let's dive deeper into RL, covering the Bellman Equations!

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Mamba Neural Network

This paper was released earlier this year, and is an alternative to the Transformer!

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Model Distillation

Let's cover model distillation, a key contribution to deep learning by Dr. Hinton.

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Intro to Multi Agent Frameworks

In this lecture, we go over the Self Organized Agent Framework for code generation!

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Mixture of Experts

The secret neural network behind GPT 4. PyTorch is a prerequisite to this lecture!

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Intro to RL - Part 1

An intro to Reinforcement Learning. Let's build agents that learn in an environment!

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Infinite Transformer . . .

Google developed a new Transformer that can process infinite context. Let's explain it.

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RL - Part 3

Let's dive into PPO, the algorithm behind RLHF (RL from Human Feedback).

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Survey of LLM RS

In this lecture, we go over options for using LLMs as RS (Recommendation Systems) ! Discriminative & Generative Models are discussed.

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Graph Neural Networks (GNNs) - Part 2

Let's implement a Graph Neural Network and train it using PyTorch Geometric!

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Image Classification

The basics of Convolutional Neural Networks, also known as CNNs.

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Vision Transformer

Transformers can be used for image recognition too! Move over CNNs . . .

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ScreenAI (Google Paper)

What if we had a Vision - Language Model specialized for user interfaces?

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Classical ML

Let's discuss the K-Means algorithm, an unsupervised clustering method!

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Graph Neural Networks (GNNs)

Let's explore the basics of GNNs, as well as the Attention Graph Network from 2018.

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ChatDev Multi Agent Framework

In this lecture, we go over the ChatDev Framework for software development!

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Sentence BERT (SBERT)

In this lecture, we go over how to train Sentence or Paragraph Embeddings - without using Token/Word Embeddings!

New Member Note 

I previously created these lectures while I was running an ML Community, in which we reviewed papers on a Discord Server.

 

This service was in the ballpark of $1000 USD and isn't offered anymore, but I'll reach out if it ever becomes available again!

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For now, enjoy these recordings as a free bonus!

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