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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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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

ML Canvas – A Visual ML Model Designer

#machinelearning #ai #deeplearning

1 min read

ML Canvas

Feb 22

Why ML Canvas is Built for ML Developers

#machinelearning #deeplearning #ai

1 min read

Feb 21

Vector Algebra

#machinelearning #ai #deeplearning

4 min read

Feb 20

Singular Value Decomposition (SVD): Part 2

#machinelearning #ai #deeplearning

3 min read

Aditya Tripathi

Mar 15

How Deep Learning is Revolutionizing Natural Language Processing (NLP)

#nlp #deeplearning #machinelearning #datascience

4 min read

Feb 19

Singular Value Decomposition (SVD)

#machinelearning #ai #deeplearning

3 min read

Feb 18

Matrix Diagonalization

#machinelearning #ai #deeplearning

3 min read

Feb 17

Eigen Decomposition of a Matrix

#ai #deeplearning #machinelearning

3 min read

NeuralLang

Mar 23

Increase Productivity with Neural DSL v0.2.4: Automatic Shape Propagation Explained

#ai #tensorflow #machinelearning #deeplearning

2 min read

Feb 28

Implementation of Mean, Variance, and Standard Deviation

#machinelearning #ai #deeplearning

2 min read

Feb 14

Orthogonal and Orthonormal Vectors in Linear Algebra

#machinelearning #deeplearning #ai

2 min read

Mar 20

Program to Find the Correlation Coefficient

#ai #machinelearning #deeplearning

2 min read

Mar 20

Kronecker-Factored Approximate Curvature (K-FAC) for Deep Learning

#deeplearning #alexnguyen #kroneckerfactored #machinelearning

15 min read

Mar 19

Covariance and Correlation

#ai #machinelearning #deeplearning

3 min read

Feb 13

Eigenspace and Eigenspectrum

#machinelearning #ai #deeplearning

3 min read

Jeremiah Adepoju

Mar 18

What is CAMEL-AI and Why is it Important?

#camelai #ai #agent #deeplearning

2 min read

Feb 12

Eigenvalues and Eigenvectors

#machinelearning #ai #deeplearning

3 min read

Aditya Tripathi

Feb 12

What is Deep Learning? A Comprehensive Guide

#datascience #ai #deeplearning #machinelearning

4 min read

Mar 17

Geometric Deep Learning: Unlocking the Power of Structured and Non-Euclidean Data - By Alex Nguyen

#deeplearning #geometricdeeplearning #machinelearning #ai

17 min read

Feb 11

Determinant of a Matrix

#machinelearning #ai #deeplearning

3 min read

NeuralLang

Mar 16

Hyperparameter Optimization Across Frameworks Made Simple - Neural DSL v0.2.3

#showdev #ai #machinelearning #deeplearning

3 min read

Feb 10

Row Echelon Form

#machinelearning #deeplearning #ai

3 min read

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