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Tutorials & Deep Dives

Comprehensive guides, from-scratch implementations, curated paper collections, and hands-on tutorials across LLMs, diffusion models, computer vision, and ML systems.

40+ Resources 1.2K+ Stars 8 Categories
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LLMs & Fine-Tuning4
Efficient Inference4
Diffusion Models3
Attention & Transformers3
Computer Vision7
ML Systems2
Foundations3
Reading Lists4
LLMs Inference Diffusion Attention Vision Systems Foundations Reading

LLMs & Fine-Tuning

From fundamentals to scaling laws — everything about large language models

4
LLM Fine-Tuning: A Complete GuideGuide
A comprehensive, chapter-by-chapter guide to LLMs — from probability basics to scaling laws, with hands-on fine-tuning code and exercises.
LLMFine-TuningScaling Laws
LLM Fine-Tune Desktop AppTutorial
PyQt5 desktop GUI for fine-tuning, evaluating, and deploying LLMs using torchtune — no command-line required.
torchtuneLoRAPyQt5
LLM Architectures & DeploymentGuide
Comprehensive guides for working with Large Language Models — architectures, training pipelines, and deployment strategies.
ArchitecturesTransformersDeployment
LoRA: From Scratch ImplementationImplementation
Low-Rank Adaptation of Large Language Models — parameter-efficient fine-tuning implemented from scratch with detailed code walkthrough.
LoRAPEFTFrom Scratch

Efficient Inference & Compression

KV cache optimization, model quantization, and LLM compression research

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KV Cache & LLM Compression Papers150+ Papers
Curated collection of 150+ research papers on KV Cache Management, KV Cache Compression, and LLM Compression for efficient inference.
KV CacheCompressionInference
Awesome Model QuantizationPapers
Curated list of papers, docs, and code about model quantization — aimed at providing comprehensive info for quantization research.
QuantizationQATGPTQ
YOLOX Quantization & DistillationTutorial
Hands-on tutorial combining YOLOX with Quantization Aware Training and Knowledge Distillation for efficient real-time object detection.
YOLOXQATKD
ONNX: Complete TutorialGuide
A comprehensive, book-style tutorial covering everything about ONNX — from fundamentals to production deployment and optimization.
ONNXDeploymentOptimization

Diffusion Models

Image generation, text diffusion, and denoising from theory to implementation

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Diffusion Language ModelsImplementation
Text generation using diffusion-style denoising — iteratively refining noisy sequences into coherent text, an alternative to autoregressive LLMs.
Diffusion LMText GenPyTorch
Reparameterization DenoisingImplementation
Implementation of diffusion-based denoising with reparameterization — organized and shared with detailed code walkthrough.
DenoisingDiffusionPyTorch
Diffusion Models: Survey & TaxonomyPapers
Comprehensive survey and taxonomy of diffusion model papers — organized by architecture, application, and training methodology.
SurveyTaxonomyResearch

Attention & Transformers

Efficient attention mechanisms, linear attention, and transformer architecture surveys

3
Attention Mechanisms: 3 SurveysGuide
Three in-depth surveys covering efficient transformer architectures, attention variants, and optimization techniques for scalable inference.
AttentionTransformersEfficiency
REGLA: Gated Linear AttentionImplementation
Refining Gated Linear Attention — efficient alternative to softmax attention for scalable sequence modeling with linear complexity.
Linear AttentionEfficientResearch
From PCA to VAETutorial
Understanding dimensionality reduction from classical PCA through autoencoders to Variational Autoencoders — theory and implementation.
PCAVAERepresentation

Computer Vision

Image enhancement, object detection, segmentation, and low-level vision

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VisionRL — RL for Computer Vision12 Modules
Complete step-by-step course: RL for image enhancement, segmentation, detection, and generation. 12 modules from foundations to capstone.
RLEnhancementDetectionGeneration
Low-Level Vision: Complete GuideGuide
Super-Resolution, denoising, deblurring, dehazing, low-light enhancement, artifact removal — end-to-end models with benchmarks.
DenoisingSuper-ResEnhancement
FlashDet: End-to-End DetectionTutorial
Complete training system with PyQt5 app — LoRA/QLoRA fine-tuning, knowledge distillation, ONNX export, INT8 quantization. 100+ FPS.
DetectionLoRAKD
YOLOv8 PyTorch ImplementationImplementation
Modular PyTorch implementation of YOLOv8 for object detection with clear architecture, training pipelines, and documentation.
YOLOv8PyTorchDetection
Feature Detection from ScratchImplementation
From-scratch implementations of classic feature detection algorithms — SIFT, SURF, ORB, Harris, and more.
FeaturesClassical CVFrom Scratch
Image Object Removal & InpaintingTutorial
Remove objects from photos including shadows and reflections using generative inpainting — diffusion-based restoration.
InpaintingGenAIDiffusion
Bayer Low-Light EnhancementImplementation
Low-light image enhancement directly on Bayer pattern data — RAW image processing with deep learning for mobile camera pipelines.
Low-LightRAWMobile

ML Systems & Production

System design, data drift, monitoring, and production ML architecture

2
ML System Design GuideGuide
Comprehensive guide to ML System Design — LLM serving, training pipelines, scaling, and real-world architecture patterns.
System DesignLLM ServingArchitecture
Data Drift in Production ML200+ Papers
Research on data drift — taxonomy (covariate/concept/label shift), mathematical formulations, monitoring architectures, and 200+ curated papers.
Data DriftMLOpsMonitoring

Foundations & Mathematics

ML research foundations, linear algebra, DSA, and courses

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ML Researcher FoundationsRoadmap
Structured, end-to-end roadmap for becoming a strong ML researcher — mathematical foundations, ML theory, deep learning, optimization.
MathOptimizationResearch
Data Structures & Algorithms170+ Stars
Well-organized repository covering core DSA from fundamentals to advanced topics — systematic learning and reference implementations.
DSAInterviewsAlgorithms
CV Interview QuestionsGuide
Curated computer vision interview questions covering CNNs, object detection, segmentation, GANs, transformers, and production deployment.
InterviewCVDeep Learning

Curated Reading Lists

Awesome lists, paper collections, and survey compilations

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Low-Level Vision Paper RecordPapers
Curated record of papers on low-level vision tasks — super-resolution, denoising, deblurring, and image restoration research.
Super-ResDenoisingPapers
Awesome Transformer AttentionPapers
Curated list of research papers on efficient attention mechanisms and transformer architectures for NLP and vision.
AttentionTransformersSurvey
Awesome VLM ArchitecturesPapers
Curated collection of Vision-Language Model architectures — from CLIP to GPT-4V, covering multi-modal learning and alignment.
VLMMulti-ModalCLIP
OCR Research PapersPapers
Collection of OCR research papers — scene text detection, recognition, and end-to-end document understanding systems.
OCRText DetectionDocuments

ML for Everyone — Complete Textbook

12 volumes covering ML theory from scratch — probability, optimization, neural networks, and beyond. Free and open-source.