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Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 3517 posts
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Speech & Audio AI Complete Guide: ASR, TTS, Whisper, Wav2Vec to Voice Synthesis
A complete guide to speech and audio AI from fundamentals to cutting-edge techniques. Master audio signal processing, Mel Spectrogram, ASR (Whisper, Wav2Vec2), TTS (Tacotron, VITS), speaker diarization, and music generat
2026-03-17 · 16 min read #speech-recognition#tts#whisper#wav2vec#audio-processingRust for AI Systems: From Ownership to High-Performance Inference Servers with Candle, PyO3, and axum
A complete Rust guide for AI infrastructure — from the ownership system and Candle ML framework to PyO3 Python integration, axum inference servers, and WebAssembly deployment.
2026-03-17 · 13 min read #rust#aisystem#candle#pyo3#polarsRobotics & AI Complete Guide: From ROS2 to Humanoid Robots
A comprehensive guide covering the fusion of robotics and AI. From ROS2, SLAM, and motion planning to computer vision, reinforcement learning-based robot control, and humanoid robot trends — with Python examples througho
2026-03-17 · 16 min read #robotics#ros2#autonomous-robot#slam#motion-planningDeep Learning Recommendation Systems Complete Guide: From Collaborative Filtering to LLM-based RecSys
A complete guide to recommendation systems from foundations to the latest deep learning techniques. Master collaborative filtering, Matrix Factorization, NCF, Two-Tower models, sequential recommendation, GNN-based approa
2026-03-17 · 18 min read #recommendation-system#collaborative-filtering#deep-learning#two-tower#llmPyTorch Internals & Advanced Optimization: autograd, torch.compile, FSDP, and Triton
A complete guide to PyTorch internals: autograd engine, torch.compile() with TorchInductor, FSDP distributed training, gradient checkpointing, and custom CUDA operations.
2026-03-17 · 10 min read #pytorch#torch-compile#fsdp#triton#mixedprecisionOperating Systems: A Complete Guide — From Processes & Memory to AI Workload Optimization
A comprehensive guide for AI engineers covering process scheduling, virtual memory, file systems, iouring, NUMA-aware memory allocation, and GPU resource isolation with cgroups.
2026-03-17 · 12 min read #operating-systems#linux#memory-management#scheduling#iouringPython Complete Guide for AI/ML: Master NumPy, Pandas, Matplotlib, and Scikit-learn
The complete guide to mastering the Python ecosystem for AI and machine learning. Master NumPy array operations, Pandas data processing, Matplotlib/Seaborn visualization, and Scikit-learn machine learning through hands-o
2026-03-17 · 22 min read #python#numpy#pandas#scikit-learn#matplotlibRAG Systems Complete Guide: Everything About Retrieval-Augmented Generation
A complete guide to mastering RAG (Retrieval-Augmented Generation) systems. From basic RAG to advanced Self-RAG, Corrective-RAG, and HyDE — covering vector databases, embedding models, chunking strategies, and reranking
2026-03-17 · 23 min read #rag#llm#vector-database#langchain#embeddingPyTorch Advanced Techniques Complete Guide: torch.compile, Custom Ops, Memory Optimization
A complete guide to mastering PyTorch advanced techniques. Covers torch.compile, custom operators, memory optimization, Gradient Checkpointing, torch.vmap, functorch, and PyTorch Profiler with hands-on examples.
2026-03-17 · 17 min read #pytorch#advanced#torch-compile#memory-optimization#custom-operatorsOpen-Source LLM Landscape Guide: Models, Tools, and Deployment in 2026
A comprehensive guide to the open-source LLM ecosystem in 2026. Covers the leading model families (Llama, Mistral, Gemma, Qwen, DeepSeek), local inference tools (Ollama, llama.cpp, vLLM), fine-tuning techniques (LoRA, QL
2026-03-17 · 20 min read #open-source#llm#llama#mistral#gemmaProbabilistic Machine Learning & Bayesian Methods: From Bayesian Inference to Gaussian Processes and Uncertainty Quantification
A comprehensive guide to probabilistic ML covering Bayesian inference, posterior distributions, MCMC, variational inference, Gaussian processes, and uncertainty quantification with MC Dropout.
2026-03-17 · 13 min read #bayesianml#probabilisticml#gaussianprocess#pymc#uncertaintyquantificationMLOps & Model Lifecycle Management: MLflow, DVC, and LLMOps Complete Guide
A comprehensive guide to ML production pipelines covering MLOps maturity models, MLflow experiment tracking, DVC data versioning, feature stores, and LLMOps.
2026-03-17 · 16 min read #mlops#mlflow#dvc#llmops#featurestoreOpen Source Community Digest: Noteworthy Projects of March 2026
A roundup of the most exciting open source projects and community highlights from March 2026.
2026-03-17 · 9 min read #opensource#github#ai-agent#developer-tools#communityNLP & Text Processing Complete Guide: BERT Fine-tuning, RAG Systems, and Multilingual Processing
A comprehensive guide to NLP and text processing covering BPE tokenization, Word2Vec, BERT fine-tuning, RAG pipelines, and Korean morpheme analysis.
2026-03-17 · 15 min read #nlp#bert#embeddings#rag#koreannlpNatural Language Processing Complete Guide: Zero to Hero - From Text Processing to LLMs
A comprehensive guide from NLP fundamentals to the latest LLMs. Learn text preprocessing, Word2Vec, RNN/LSTM, Attention, Transformer, BERT, and GPT step by step with practical code examples.
2026-03-17 · 33 min read #nlp#natural-language-processing#transformer#bert#gptPower Electronics & Electric Machinery Guide: From DC-DC Converters to BLDC Motor Control
A comprehensive guide to power electronics and electric machinery for EE students. Covers DC-DC converters (Buck/Boost), inverters, PWM control, transformers, induction motors, and BLDC motor control with Python simulati
2026-03-17 · 15 min read #power-electronics#electric-machinery#dc-dc-converter#inverter#motor-controlMathematical Optimization for Machine Learning: From Adam to Convex Optimization and ZeRO
A comprehensive guide to ML training optimization covering SGD, Adam, AdamW, Lion optimizer, cosine annealing scheduling, Focal Loss, InfoNCE, and ZeRO optimizer.
2026-03-17 · 12 min read #optimization#adamw#learning-rate-scheduling#loss-functions#convex-optimizationMeta-Learning and Few-Shot Learning Complete Guide: MAML, Prototypical Networks, In-Context Learning
A complete guide to mastering meta-learning and few-shot learning. From "learning to learn" to MAML, Prototypical Networks, Matching Networks, Reptile, and In-Context Learning in LLMs — with hands-on code.
2026-03-17 · 24 min read #meta-learning#few-shot-learning#maml#prototypical-networks#in-context-learningNetwork Engineering & Security Master Guide: From TCP/IP to Service Mesh and AI Serving Networks
A complete networking guide for AI engineers covering TCP/IP fundamentals, gRPC, Istio service mesh, Zero Trust security, and real-time LLM streaming.
2026-03-17 · 11 min read #networking#grpc#tls#service-mesh#istioLLM Evaluation and Benchmarking Guide: Measuring What Actually Matters
A comprehensive guide to LLM evaluation and benchmarking. Covers standard academic benchmarks (MMLU, HELM, MT-Bench), production evaluation pipelines, LLM-as-judge, human evaluation, RAG evaluation, safety testing, and b
2026-03-17 · 18 min read #llm#evaluation#benchmark#mmlu#helm