๐ค๐ง The Transformer Architecture: How Attention Revolutionized Deep Learning
๐๏ธ 11 Nov 2025
๐ AI News & Trends
The field of artificial intelligence has witnessed a remarkable evolution and at the heart of this transformation lies the Transformer architecture. Introduced by Vaswani et al. in 2017, the paper โAttention Is All You Needโ redefined the foundations of natural language processing (NLP) and sequence modeling. Unlike its predecessors โ recurrent and convolutional neural networks, ...
#TransformerArchitecture #AttentionMechanism #DeepLearning #NaturalLanguageProcessing #NLP #AIResearch
๐๏ธ 11 Nov 2025
๐ AI News & Trends
The field of artificial intelligence has witnessed a remarkable evolution and at the heart of this transformation lies the Transformer architecture. Introduced by Vaswani et al. in 2017, the paper โAttention Is All You Needโ redefined the foundations of natural language processing (NLP) and sequence modeling. Unlike its predecessors โ recurrent and convolutional neural networks, ...
#TransformerArchitecture #AttentionMechanism #DeepLearning #NaturalLanguageProcessing #NLP #AIResearch
โค5
This is not a full-fledged course with a unified program, but a collection of nine separate videos on PyTorch and neural networks gathered in one playlist.
Inside, there are materials of different levels and formats that are suitable for selective study of topics, practice, and a general understanding of the direction.
What's here:
The collection is suitable for those who are already familiar with Python and want to selectively study PyTorch without a strict study plan โ get it here.๐ฎ Introductory videos on PyTorch and the basics of neural networks;๐ฎ Practical analyses with code writing and project examples;๐ฎ Materials on computer vision and working with medical images;๐ฎ Examples of creating chat bots and models on PyTorch;๐ฎ Analyses of large language models and generative neural networks;๐ฎ Examples of training agents and reinforcement tasks;๐ฎ Videos from different authors without a general learning logic.
https://www.youtube.com/playlist?list=PLp0BA-8NZ4bhBNWvUBPDztbzLar9Jcgd-
tags: #pytorch #DeepLearning #python
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โค11๐2๐ฅ1
โก๏ธ All cheat sheets for programmers in one place.
There's a lot of useful stuff inside: short, clear tips on languages, technologies, and frameworks.
No registration required and it's free.
https://overapi.com/
#python #php #Database #DataAnalysis #MachineLearning #AI #DeepLearning #LLMS
https://t.iss.one/CodeProgrammerโก๏ธ
There's a lot of useful stuff inside: short, clear tips on languages, technologies, and frameworks.
No registration required and it's free.
https://overapi.com/
#python #php #Database #DataAnalysis #MachineLearning #AI #DeepLearning #LLMS
https://t.iss.one/CodeProgrammer
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โค13๐1
Deep Delta Learning
Read Free:
https://www.k-a.in/DDL.html
#DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience
https://t.iss.one/CodeProgrammer
Read Free:
https://www.k-a.in/DDL.html
#DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience
https://t.iss.one/CodeProgrammer
โค8๐3๐ฏ2
Machine Learning Roadmap 2026
#MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #DataAnalysis #LLM #python
https://t.iss.one/CodeProgrammer
#MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #DataAnalysis #LLM #python
https://t.iss.one/CodeProgrammer
โค11๐ฅ2๐1๐1
Collection of books on machine learning and artificial intelligence in PDF format
Repo: https://github.com/Ramakm/AI-ML-Book-References
#MACHINELEARNING #PYTHON #DATASCIENCE #DATAANALYSIS #DeepLearning
๐ @codeprogrammer
Repo: https://github.com/Ramakm/AI-ML-Book-References
#MACHINELEARNING #PYTHON #DATASCIENCE #DATAANALYSIS #DeepLearning
๐ @codeprogrammer
โค16๐2๐1๐1
DS Interview.pdf
1.6 MB
Data Science Interview questions
#DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience #DataAnalysis #LLM #InterviewQuestions
https://t.iss.one/CodeProgrammer
#DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience #DataAnalysis #LLM #InterviewQuestions
https://t.iss.one/CodeProgrammer
โค10๐2๐ฅ2
A full-fledged educational course has been published on the university's website: 24 lectures, practical tasks, homework assignments, and a collection of materials for self-study.
The program includes modern neural network architectures, generative models, transformers, inference, and other key topics.
A great opportunity to study deep learning based on the structure of a top university, free of charge and without simplifications โ let's learn here.
https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/resources/lecture-videos/
tags: #python #deeplearning
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โค12๐2๐2
Kaggle offers interactive courses that will help you quickly understand the key topics of DS and ML.
The format is simple: short lessons, practical tasks, and a certificate upon completion โ all for free.
Inside:
โข basics of Python for data analysis;
โข machine learning and working with models;
โข pandas, SQL, visualization;
โข advanced techniques and practical cases.
Each course takes just 3โ5 hours and immediately provides practical knowledge for work.
tags: #ML #DEEPLEARNING #AI
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โค8๐ฏ3
If you want to understand AI not through "vacuum" courses, but through real open-source projects - here's a top list of repos that really lead you from the basics to practice:
1) Karpathy โ Neural Networks: Zero to Hero
The most understandable introduction to neural networks and backprop "in layman's terms"
https://github.com/karpathy/nn-zero-to-hero
2) Hugging Face Transformers
The main library of modern NLP/LLM: models, tokenizers, fine-tuning
https://github.com/huggingface/transformers
3) FastAI โ Fastbook
Practical DL training through projects and experiments
https://github.com/fastai/fastbook
4) Made With ML
ML as an engineering system: pipelines, production, deployment, monitoring
https://github.com/GokuMohandas/Made-With-ML
5) Machine Learning System Design (Chip Huyen)
How to build ML systems in real business: data, metrics, infrastructure
https://github.com/chiphuyen/machine-learning-systems-design
6) Awesome Generative AI Guide
A collection of materials on GenAI: from basics to practice
https://github.com/aishwaryanr/awesome-generative-ai-guide
7) Dive into Deep Learning (D2L)
One of the best books on DL + code + assignments
https://github.com/d2l-ai/d2l-en
Save it for yourself - this is a base on which you can really grow into an ML/LLM engineer.
#Python #datascience #DataAnalysis #MachineLearning #AI #DeepLearning #LLMS
https://t.iss.one/CodeProgrammer
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