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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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NeuralLang

Mar 23

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

#ai #tensorflow #machinelearning #deeplearning

2 min read

Mar 20

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

#deeplearning #alexnguyen #kroneckerfactored #machinelearning

15 min read

Aditya Tripathi

Mar 19

The Future of Deep Learning: Trends and Predictions for 2025

#datascience #deeplearning #python #webdev

5 min read

Mar 18

Confidence Interval

#ai #machinelearning #deeplearning

4 min read

John

Mar 18

Deep Learning Meets OCR: My FastAPI-Powered Document Cleaning Tool

#webdev #fastapi #python #deeplearning

3 min read

Mar 17

Hypothesis Testing

#ai #machinelearning #deeplearning

4 min read

HoangP

Mar 17

An open-source library about Implicit Deep Learning

#opensource #deeplearning

1 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

Aleksei Aleinikov

Mar 21

🧠 How a Deep Learning Framework Actually Works (From-Scratch PyTorch Clone)

#machinelearning #pytorch #deeplearning #python

1 min read

Diyorbek Umaraliyev

Mar 16

Building and Deploying an MNIST Digit Recognition App with PyTorch and Streamlit

#ai #pytorch #deeplearning

2 min read

Mar 20

Program to Find the Correlation Coefficient

#ai #machinelearning #deeplearning

2 min read

Mar 19

Covariance and Correlation

#ai #machinelearning #deeplearning

3 min read

Mar 14

Bias-Variance Tradeoff

#ai #machinelearning #deeplearning

3 min read

SkillBoostTrainer

Mar 14

The Evolution of AI Architecture: Designing Scalable and Intelligent Systems

#ai #deeplearning #cloudcomputing #machinelearning

2 min read

SkillBoostTrainer

Mar 14

Advancing AI with Machine Learning Engineering

#ai #machinelearning #deeplearning #webdev

2 min read

Jeremiah Adepoju

Mar 18

What is CAMEL-AI and Why is it Important?

#camelai #ai #agent #deeplearning

2 min read

Mar 13

Bias and Variance

#machinelearning #ai #deeplearning

2 min read

Jaykumar Bhaumikbhai Patel

Mar 17

Unlocking AI Potential with Gemma 3: A Comprehensive Guide for Developers, Businesses, and Innovators

#ai #deeplearning #machinelearning #llm

3 min read

Mar 12

True Error vs Sample Error

#machinelearning #ai #deeplearning

3 min read

Mar 17

Swine Transformers

#ai #deeplearning

1 min read

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

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

Shaheryar

Mar 7

Why Use RAG? Benefits Over Standard LLMs

#ai #machinelearning #deeplearning

2 min read

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