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Please ensure that any post tagged with #deeplearning is primarily on deep learning while generally can be on machine learning, data science, AI, CS, etc.

Please also be sure that your content adheres to the DEV Code of Conduct and that your comments are constructive and kind.

Conventional machine learning techniques are limited in their ability to automatically transform the raw unstructured data into a suitable internal representation. Deep learning methods are representation learning methods with multiple levels of representation, obtained by composing several simple but non-linear modules that each transform the representation at one level (starting with the raw input) into a representation at a higher, slightly more abstract level - to put it simply - Neural Networks. With the composition of enough such transformations, very complex functions can be learned - a universal approximator.
If you want to share something primarily on deep learning techniques please use #deeplearning tag.

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Dinesh Kumar Sarangapani

Oct 10

Section 3a: f-divergences

#ai #deeplearning #machinelearning

8 min read

Dinesh Kumar Sarangapani

Oct 10

Section 1: The dataset and the problem

#ai #deeplearning #machinelearning

6 min read

Akash

Oct 9

From Attention to a Working Language Model

#machinelearning #deeplearning #llm #nlp

13 min read

Freddy Lécué for Daily Context

Oct 11

Why Smaller AI Models Can Win in the Enterprise

#aie #machinelearning #gpu #deeplearning

2 min read

Felipe 0liveira

Oct 9

GRPO leaves the chatbot and starts fixing OCR, while DPO and GRPO get debugged from the inside

#ai #deeplearning #llm #machinelearning

6 min read

Prabhakar Chaudhary

Oct 9

EmbeddingGemma 2: How Google's Open Multimodal Embedding Model Works

#ai #machinelearning #deeplearning #opensource

5 min read

Daniel Sam Pete Thiyagu

Oct 8

Only 3% of the Brain Wakes Up: The Mixture-of-Experts Playbook Behind September's Biggest Models

#ai #machinelearning #deeplearning #llm

6 min read

Oct 8

Fine-tuning EfficientNetB0 for 104 flower classes: validation vs held-out test scores, honestly

#machinelearning #python #deeplearning

2 min read

Prabhakar Chaudhary

Oct 8

Fault-Tolerant Foundation Models: Training LLMs to Thrive on Unreliable Hardware

#ai #machinelearning #deeplearning #python

5 min read

Daniel Sam Pete Thiyagu

Oct 7

The Model That Doesn't Talk

#ai #machinelearning #deeplearning #datascience

5 min read

Sergey Boyarchuk

Oct 7

Burn Tensor Library Enhances API Stability, Performance, and Developer Experience for 1.0 Release

#tensor #rust #deeplearning #performance

14 min read

Gabby Six

Oct 6

Dust: The Radical Idea of Training AI Without Backpropagation

#ai #machinelearning #deeplearning #research

4 min read

cz

Oct 6

Understanding Prism: Dynamic Sparse Attention for Joint Video-Audio Generation

#ai #machinelearning #videogeneration #deeplearning

4 min read

Daniel Sam Pete Thiyagu

Oct 5

1,107 Tokens Per Second: The LLM That Doesn't Type

#ai #llm #machinelearning #deeplearning

5 min read

cognitalk

Oct 6

One Brain, Any Body: Google DeepMind's Keerthana on Gemini ER2 | 谷歌DeepMind Gemini Robotics 2 与通用机器人现状深度访谈

#ai #deeplearning #machinelearning #robotics

2 min read

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