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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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Rost

Sep 8

What Comes After LLMs? Mamba, Diffusion & World Models

#ai #llm #architecture #deeplearning

11 min read

Wesam Khallaf — Author of PyTorch From Ground Up

Sep 8

What Your Loss Function Actually Tells the Model: MSE, Cross-Entropy, and the softmax Bug That Trains Anyway

#pytorch #deeplearning #machinelearning #beginners

13 min read

Sep 8

Neural Networks: Inspired by the Brain, Built for Data

#ai #deeplearning #datascience #machinelearning

10 min read

howcani howcani

Sep 8

We measured sharpness during loss spikes. The instrument started returning negative numbers.

#machinelearning #deeplearning #ai

3 min read

Anushka S Raghunandan

Sep 7

What I Learned Building a Mini TensorRT

#computerscience #deeplearning #machinelearning #performance

3 min read

Sep 7

AI LinkedIn headshot explained, a developer teardown

#ai #deeplearning #machinelearning #software

6 min read

Sep 6

Neural Networks: Weights, Activation, and Backpropagation

#machinelearning #beginners #deeplearning #pytorch

5 min read

howcani howcani

Sep 7

Four Mechanisms Were Blamed for Loss Spikes in 2026. We Tested All Four at Once. None of Them Alone Causes Spikes.

#ai #machinelearning #deeplearning

3 min read

zeromathai

Sep 6

Inverse Problems: Why Predicting Backward Is Harder Than It Looks

#machinelearning #generativeai #inference #deeplearning

6 min read

Baaz

Sep 6

The Use of AI in Computer Vision

#ai #deeplearning #machinelearning

3 min read

howcani howcani

Sep 5

Every Greedy Metric Said the Model Was Improving. Then pass@64 Fell From 0.83 to 0.19

#ai #deeplearning #llm #machinelearning

4 min read

Sanya

Sep 5

AI Safety Researcher 工具箱：数据投毒防御、可解释性、进度追踪与判断力

#ai #machinelearning #deeplearning #aisafety

2 min read

Agbo, Daniel Onuoha

Sep 4

The Next Phase of Vision-Language Navigation

#deeplearning #ai #machinelearning #robotics

9 min read

Secret123

Sep 4

Imag-Eval

#ai #machinelearning #deeplearning #computervision

1 min read

Sep 3

Neve - Towards a Unified Programming Model for the Complete Deep Learning Stack

#deeplearning #machinelearning #programming

8 min read

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