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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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Marita P

Oct 5

How AI Rap Duo Video Generators Work Under the Hood (and How to Pick One)

#ai #deeplearning #machinelearning

3 min read

Kathir

Oct 3

DAY 1 - GENERATIVE AI

#ai #deeplearning #llm #machinelearning

8 min read

Oct 3

RL 5: Learning Automata and stochastic environments (1961–1974)

#rl #machinelearning #deeplearning #ai

21 min read

Oct 3

How AI Learns: Forward Pass and Loss Explained with 2 + 1

#ai #machinelearning #deeplearning #beginners

2 min read

Oct 1

Understanding Neural Networks: The Core Idea

#ai #deeplearning #machinelearning

11 min read

Prabhakar Chaudhary

Oct 1

UniEvo-VL: On-Policy Self-Distillation for Multimodal Image Generation

#ai #machinelearning #deeplearning #computervision

5 min read

Mira Ceti

Oct 1

RoPE vs sinusoidal positional encoding, measured: 55 logits of drift against 0.0005

#machinelearning #deeplearning #pytorch #python

7 min read

Sep 30

Why AI Lies Without Knowing It’s Lying | Victor Amit

#ai #machinelearning #llm #deeplearning

21 min read

Prabhakar Chaudhary

Sep 30

REAL-Q: How Dynamic Gradient Descent Fixes the Core Flaw in LLM Quantization

#machinelearning #deeplearning #llm #python

5 min read

Utsav D

Sep 29

I Built a Tiny Neural Network From Scratch in Python — No PyTorch

#deeplearning #machinelearning #python #tutorial

6 min read

Aleksei Romanov for g factor

Oct 2

We Tried ISO-AdamW. AdamW Kept Its Job.

#machinelearning #llm #deeplearning #ai

11 min read

Prabhakar Chaudhary

Sep 28

Bonsai 2 27B: How Ternary Weights and a Hadamard Rotation Compress a 27B Model to 5.9 GB

#ai #machinelearning #deeplearning #opensource

5 min read

mi ni

Sep 28

What I Learned Building a Two-Image AI Virtual Try-On Workflow for Holiday Outfits

#ai #deeplearning #machinelearning

6 min read

Wesam Khallaf — Author of PyTorch From Ground Up

Sep 26

nn.Module Explained: The Same Model Built with Raw Tensors and with nn.Module

#pytorch #deeplearning #beginners #machinelearning

8 min read

Sep 25

RL 4: Early heuristics and the birth of Temporal Difference learning (1959–1968)

#rl #ai #machinelearning #deeplearning

15 min read

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