Data Science Machine Learning Data Analysis
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This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning

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Data Science Machine Learning Data Analysis
37.3K subscribers
Data Science Machine Learning Data Analysis
๐ŸŒŸ Vision Transformer (ViT) Tutorial โ€“ Part 5: Efficient Vision Transformers โ€“ MobileViT, TinyViT & Edge Deployment

Read lesson: https://hackmd.io/@husseinsheikho/vit-5

#MobileViT #TinyViT #EfficientViT #EdgeAI #ModelOptimization #ONNX #TensorRT #TorchServe #DeepLearning #ComputerVision #Transformers

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Data Science Machine Learning Data Analysis
๐ŸŒŸ Vision Transformer (ViT) Tutorial โ€“ Part 6: Vision Transformers in Production โ€“ MLOps, Monitoring & CI/CD

Learn more: https://hackmd.io/@husseinsheikho/vit-6

#MLOps #ModelMonitoring #CIforML #MLflow #WandB #Kubeflow #ProductionAI #DeepLearning #ComputerVision #Transformers #AIOps

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Data Science Machine Learning Data Analysis
๐ŸŒŸ Vision Transformer (ViT) Tutorial โ€“ Part 7: The Future of Vision Transformers โ€“ Multimodal, 3D, and Beyond

Learn: https://hackmd.io/@husseinsheikho/vit-7

#FutureOfViT #MultimodalAI #3DViT #TimeSformer #PaLME #MedicalAI #EmbodiedAI #RetNet #Mamba #NextGenAI #DeepLearning #ComputerVision #Transformers

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Data Science Machine Learning Data Analysis
๐Ÿ”ฅ Master Vision Transformers with 65+ MCQs! ๐Ÿ”ฅ

Are you preparing for AI interviews or want to test your knowledge in Vision Transformers (ViT)?

๐Ÿง  Dive into 65+ curated Multiple Choice Questions covering the fundamentals, architecture, training, and applications of ViT โ€” all with answers!

๐ŸŒ Explore Now: https://hackmd.io/@husseinsheikho/vit-mcq

๐Ÿ”น Table of Contents
Basic Concepts (Q1โ€“Q15)
Architecture & Components (Q16โ€“Q30)
Attention & Transformers (Q31โ€“Q45)
Training & Optimization (Q46โ€“Q55)
Advanced & Real-World Applications (Q56โ€“Q65)
Answer Key & Explanations

#VisionTransformer #ViT #DeepLearning #ComputerVision #Transformers #AI #MachineLearning #MCQ #InterviewPrep


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Data Science Machine Learning Data Analysis
Forwarded from Python | Machine Learning | Coding | R
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Data Science Machine Learning Data Analysis
Forwarded from Python | Machine Learning | Coding | R
Join our WhatsApp channel

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Python | Machine Learning | Data Science | WhatsApp Channel
Python | Machine Learning | Data Science WhatsApp Channel. Welcome to our official WhatsApp Channel โ€“ your daily dose of AI, Python, and cutting-edge technology!

Here, we share:

Python tutorials and ready-to-use code snippets

AI & machine learning tipsโ€ฆ
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Data Science Machine Learning Data Analysis
Forwarded from Python | Machine Learning | Coding | R
๐Ÿš€ Become an Agentic AI Builder โ€” Free 12โ€‘Week Certification by Ready Tensor

Ready Tensorโ€™s Agentic AI Developer Certification is a free, project first 12โ€‘week program designed to help you build and deploy real-world agentic AI systems. You'll complete three portfolio-ready projects using tools like LangChain, LangGraph, and vector databases, while deploying production-ready agents with FastAPI or Streamlit.

The course focuses on developing autonomous AI agents that can plan, reason, use memory, and act safely in complex environments. Certification is earned not by watching lectures, but by building โ€” each project is reviewed against rigorous standards.

You can start anytime, and new cohorts begin monthly. Ideal for developers and engineers ready to go beyond chat prompts and start building true agentic systems.

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โค1
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Data Science Machine Learning Data Analysis
๐Ÿ“˜ Ultimate Guide to Graph Neural Networks (GNNs): Part 1 โ€” Foundations of Graph Theory & Why GNNs Revolutionize AI

Duration: ~45 minutes reading time | Comprehensive beginner-to-advanced introduction

Let's start: https://hackmd.io/@husseinsheikho/GNN-1

#GraphNeuralNetworks #GNN #MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #GraphTheory #ArtificialIntelligence #PyTorchGeometric #NodeClassification #LinkPrediction #GraphRepresentation #AIforBeginners #AdvancedAI
๏ปฟ
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Data Science Machine Learning Data Analysis
๐Ÿ“˜ Ultimate Guide to Graph Neural Networks (GNNs): Part 2 โ€” The Message Passing Framework: Mathematical Heart of All GNNs

Duration: ~60 minutes reading time | Comprehensive deep dive into the core mechanism powering modern GNNs

Let's study: https://hackmd.io/@husseinsheikho/GNN-2

#GraphNeuralNetworks #GNN #MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #GraphTheory #ArtificialIntelligence #PyTorchGeometric #MessagePassing #GraphAlgorithms #NodeClassification #LinkPrediction #GraphRepresentation #AIforBeginners #AdvancedAI

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Data Science Machine Learning Data Analysis
๐Ÿ“• Ultimate Guide to Graph Neural Networks (GNNs): Part 3 โ€” Advanced GNN Architectures: Transformers, Temporal Networks & Geometric Deep Learning

Duration: ~60 minutes reading time | Comprehensive deep dive into cutting-edge GNN architectures

๐Ÿ†˜ Read: https://hackmd.io/@husseinsheikho/GNN-3

#GraphNeuralNetworks #GNN #MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #GraphTheory #ArtificialIntelligence #PyTorchGeometric #GraphTransformers #TemporalGNNs #GeometricDeepLearning #AdvancedGNNs #AIforBeginners #AdvancedAI


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Data Science Machine Learning Data Analysis
๐Ÿ“˜ Ultimate Guide to Graph Neural Networks (GNNs): Part 4 โ€” GNN Training Dynamics, Optimization Challenges, and Scalability Solutions

Duration: ~45 minutes reading time | Comprehensive guide to training GNNs effectively at scale

Part 4-A: https://hackmd.io/@husseinsheikho/GNN4-A

Part4-B: https://hackmd.io/@husseinsheikho/GNN4-B

#GraphNeuralNetworks #GNN #MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #GraphTheory #ArtificialIntelligence #PyTorchGeometric #GNNOptimization #ScalableGNNs #TrainingDynamics #AIforBeginners #AdvancedAI


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Data Science Machine Learning Data Analysis
๐Ÿ“˜ Ultimate Guide to Graph Neural Networks (GNNs): Part 5 โ€” GNN Applications Across Domains: Real-World Impact in 30 Minutes

Duration: ~30 minutes reading time | Practical guide to GNN applications with concrete ROI metrics

Link: https://hackmd.io/@husseinsheikho/GNN-5

#GraphNeuralNetworks #GNN #MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #GraphTheory #ArtificialIntelligence #RealWorldApplications #HealthcareAI #FinTech #DrugDiscovery #RecommendationSystems #ClimateAI

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Data Science Machine Learning Data Analysis
๐Ÿ“˜ Ultimate Guide to Graph Neural Networks (GNNs): Part 6 โ€” Advanced Frontiers, Ethics, and Future Directions

Duration: ~50 minutes reading time | Cutting-edge insights on where GNNs are headed

Let's read: https://hackmd.io/@husseinsheikho/GNN-6

#GraphNeuralNetworks #GNN #MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #GraphTheory #ArtificialIntelligence #FutureOfGNNs #EmergingResearch #EthicalAI #GNNBestPractices #AdvancedAI #50MinuteRead

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Data Science Machine Learning Data Analysis
๐Ÿ“˜ Ultimate Guide to Graph Neural Networks (GNNs): Part 7 โ€” Advanced Implementation, Multimodal Integration, and Scientific Applications

Duration: ~60 minutes reading time | Deep dive into cutting-edge GNN implementations and applications

Read: https://hackmd.io/@husseinsheikho/GNN7

#GraphNeuralNetworks #GNN #MachineLearning #DeepLearning #AI #NeuralNetworks #DataScience #GraphTheory #ArtificialIntelligence #AdvancedGNNs #MultimodalLearning #ScientificAI #GNNImplementation #60MinuteRead

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Data Science Machine Learning Data Analysis
PyTorch Masterclass: Part 1 โ€“ Foundations of Deep Learning with PyTorch

Duration: ~120 minutes

Link: https://hackmd.io/@husseinsheikho/pytorch-1

#PyTorch #DeepLearning #MachineLearning #AI #NeuralNetworks #DataScience #Python #Tensors #Autograd #Backpropagation #GradientDescent #AIForBeginners #PyTorchTutorial #MachineLearningEngineer


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Data Science Machine Learning Data Analysis
PyTorch Masterclass: Part 2 โ€“ Deep Learning for Computer Vision with PyTorch

Duration: ~60 minutes

Link: https://hackmd.io/@husseinsheikho/pytorch-2

#PyTorch #ComputerVision #CNN #DeepLearning #TransferLearning #CIFAR10 #ImageClassification #DataLoaders #Transforms #ResNet #EfficientNet #PyTorchVision #AI #MachineLearning #ConvolutionalNeuralNetworks #DataAugmentation #PretrainedModels


https://t.iss.one/DataScienceM ๐Ÿ’ฏ
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Data Science Machine Learning Data Analysis
Forwarded from Python | Machine Learning | Coding | R
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๐Ÿฅ‡ This repo is like gold for every data scientist!

โœ… Just open your browser; a ton of interactive exercises and real experiences await you. Any question about statistics, probability, Python, or machine learning, you'll get the answer right there! With code, charts, even animations. This way, you don't waste time, and what you learn really sticks in your mind!

โฌ…๏ธ Data science statistics and probability topics
โฌ…๏ธ Clustering
โฌ…๏ธ Principal Component Analysis (PCA)
โฌ…๏ธ Bagging and Boosting techniques
โฌ…๏ธ Linear regression
โฌ…๏ธ Neural networks and more...


โ”Œ ๐Ÿ“‚ Int Data Science Python Dash
โ”” ๐Ÿฑ GitHub-Repos

๐Ÿ‘‰ @codeprogrammer
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Data Science Machine Learning Data Analysis
PyTorch Masterclass: Part 3 โ€“ Deep Learning for Natural Language Processing with PyTorch

Duration: ~120 minutes

Link A: https://hackmd.io/@husseinsheikho/pytorch-3a

Link B: https://hackmd.io/@husseinsheikho/pytorch-3b

#PyTorch #NLP #RNN #LSTM #GRU #Transformers #Attention #NaturalLanguageProcessing #TextClassification #SentimentAnalysis #WordEmbeddings #DeepLearning #MachineLearning #AI #SequenceModeling #BERT #GPT #TextProcessing #PyTorchNLP

https://t.iss.one/DataScienceM โš ๏ธ
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Data Science Machine Learning Data Analysis
๐ƒ๐š๐ญ๐š ๐‚๐ฅ๐ž๐š๐ง๐ข๐ง๐  ๐ข๐ง ๐๐ฒ๐ญ๐ก๐จ๐ง: ๐Ÿ๐Ÿ’ ๐Œ๐ฎ๐ฌ๐ญ-๐Š๐ง๐จ๐ฐ ๐’๐ญ๐ž๐ฉ๐ฌ ๐Ÿ (Pandas)

https://t.iss.one/DataScienceM โœ…
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Data Science Machine Learning Data Analysis
DS INTERVIEW.pdf
16.6 MB
800+ Data Science Interview Questions โ€“ A Must-Have Resource for Every Aspirant

Breaking into the data science field is challengingโ€”not because of a lack of opportunities, but because of how thoroughly you need to prepare.

This document, curated by Steve Nouri, is a goldmine of 800+ real-world interview questions covering:
-Statistics
-Data Science Fundamentals
-Data Analysis
-Machine Learning
-Deep Learning
-Python & R
-Model Evaluation & Optimization
-Deployment Strategies
โ€ฆand much more!

https://t.iss.one/CodeProgrammer ๐Ÿ”ฐ
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