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Deep Learning

This tag is for discussing, sharing articles, and asking questions primarily on deep learning - a subfield of machine learning.

about #deeplearning

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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Mar 12

Comprehensive Guide to Deep Learning Intrinsic Metrics

#deeplearning #intrinsicmetric #machinelearning #alexnguyen

55 min read

Shaheryar

Mar 11

What Are Embeddings? How They Help in RAG

#ai #vectordatabase #deeplearning #rag

3 min read

NeuralLang

Mar 10

Neural DSL v0.2.2 Release Notes

#ai #opensource #deeplearning #machinelearning

2 min read

Shaheryar

Mar 10

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗩𝗲𝗰𝘁𝗼𝗿 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀: 𝗧𝗵𝗲 𝗕𝗮𝗰𝗸𝗯𝗼𝗻𝗲 𝗼𝗳 𝗥𝗔𝗚 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹

#ai #deeplearning #machinelearning #vectordatabase

3 min read

Shaheryar

Mar 9

Key Use Cases of RAG: From Chatbots to Research Assistants

#ai #machinelearning #deeplearning #rag

3 min read

Aditya Tripathi

Mar 8

Swift for AI: The Future of Machine Learning on Apple Devices

#datascience #ai #deeplearning #machinelearning

5 min read

Mar 7

Linear Regression

#machinelearning #ai #deeplearning

4 min read

Beingana Jim Junior

Mar 8

An Introduction to Supervised Learning Models

#ai #machinelearning #deeplearning #beginners

4 min read

Shaheryar

Mar 7

Why Use RAG? Benefits Over Standard LLMs

#ai #machinelearning #deeplearning

2 min read

Mar 5

Probability & its Distribution

#machinelearning #ai #deeplearning

3 min read

Mar 6

Sampling Distributions and Statistical Tests

#machinelearning #ai #deeplearning

3 min read

Mar 4

Descriptive and Inferential Statistics

#machinelearning #ai #deeplearning

3 min read

Mohcen

Mar 4

A Comprehensive Guide to Machine Learning: Types, Algorithms and Applications

#deeplearning #ai #machinelearning

5 min read

Mar 4

How to Create a Voice Cloning AI Model for Realistic Speech Synthesis

#ai #deeplearning #voicecloning #texttospeech

3 min read

Shaheryar

Mar 4

How Does RAG Differ from Traditional NLP Models?

#ai #machinelearning #nlp #deeplearning

3 min read

Mar 2

How to Use AI for Real-Time Speech Recognition and Transcription

#ai #whisper #deeplearning #speechrecognizion

3 min read

Mar 3

Descriptive Statistics

#machinelearning #ai #deeplearning

2 min read

Ikechukwu John Uche

Feb 27

Windows 11 Virtual Machine Set Up on Microsoft Azure

#aws #career #deeplearning #css

6 min read

Feb 26

Statistics Cheatsheet – A Handy Guide for Enthusiasts

#datascience #statistics #deeplearning #machinelearning

16 min read

Feb 25

Maxima and Minima

#machinelearning #ai #deeplearning

3 min read

Feb 24

Differentiation

#deeplearning #machinelearning #ai

4 min read

Shobhit Agarwal

Feb 24

Grok 3 vs ChatGPT vs DeepSeek: I Spent $30 for an In-Depth Analysis

#grok3 #deeplearning #generativeai #chatgpt

1 min read

Feb 23

Classification vs Object detection vs Segmentation

#machinelearning #computervision #deeplearning #learning

1 min read

ML Canvas

Feb 22

Why ML Canvas is Built for ML Developers

#machinelearning #deeplearning #ai

1 min read

ML Canvas

Feb 22

ML Canvas – A Visual ML Model Designer

#machinelearning #ai #deeplearning

1 min read

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