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Categories

All (82)

Algorithms (1)

Autoencoder (1)

Bayesian Inference (3)

Convolutional Neural Networks (4)

Deep Learning (3)

Fundamentals (5)

Generative Adversarial Networks (8)

Generative Models (1)

History (1)

Image Classification (1)

Information Theory (5)

Language Models (4)

Large Language Models (13)

Machine Translation (9)

Object Detection (17)

Recurrent Neural Networks (2)

Segmentation (2)

Self-Driving Cars (4)

Sequence Modeling (1)

Transformer (8)

Vision Transformer (3)

VAE: Variational Auto-Encoder (2013)

Understanding the Auto-Encoding Variational Bayes Paper

CLIP: Learning Transferable Visual Models From Natural Language Supervision (2021)

Bridging the Gap Between Vision and Language - A Look at OpenAI’s CLIP Model

LLaMA (2023)

Open and Efficient Foundation Language Models

SwiGLU: GLU Variants Improve Transformer (2020)

ReGLU, GEGLU, SwiGLU

GLU: Gated Linear Unit (2016)

Language Modeling with Gated Convolutional Networks

Adaptive Softmax (2016)

Efﬁcient softmax approximation for GPUs

Toolformer (2023-02)

Language Models Can Teach Themselves to Use Tools

Why Can GPT Learn In-Context?

Language Models Secretly Perform Gradient Descent as Meta-Optimizers

Hands-on Deep Learning with PyTorch

A Series Of YouTube Video Lectures

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