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Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 3517 posts
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Autonomous Vehicle AI: 3D Perception, BEVFormer, and End-to-End Learning
A complete guide to autonomous driving AI: LiDAR PointNet++, BEVFormer camera perception, 3D object detection and tracking, behavior prediction, CARLA simulation, and Tesla FSD imitation learning.
2026-03-17 · 13 min read #autonomous-vehicles#bevformer#lidar#sensor-fusion#carlaAI Development Environment Complete Guide: From GPU Server Setup to Jupyter, VS Code, Docker
A complete guide to AI research and development environments. Step-by-step coverage of CUDA driver installation, virtual environment management, advanced JupyterLab usage, VS Code AI extensions, Docker GPU containers, an
2026-03-17 · 20 min read #development-environment#jupyter#vscode#docker#gpuElectronic Circuits Complete Guide: From Diodes to Op-Amps
A comprehensive guide to electronic circuits for EE students. Covers diodes, BJT/MOSFET transistors, operational amplifiers, amplifier design, and filter circuits with SPICE simulation and Python examples.
2026-03-17 · 16 min read #electronic-circuits#analog-electronics#diode#transistor#op-ampData Engineering & AI Pipeline Guide: From Apache Spark to Kafka
A comprehensive guide to data engineering for AI. Covers Apache Spark, Kafka, Airflow, dbt, Delta Lake, and Feature Stores for designing and implementing large-scale data pipelines.
2026-03-17 · 12 min read #data-engineering#apache-spark#kafka#airflow#dbtAlgorithms & Data Structures: From Complexity Analysis to AI/ML Algorithms
A complete guide to algorithms for AI engineers and coding interview preparation — covering Big-O complexity analysis, graph algorithms, dynamic programming, k-d trees, LSH, and more.
2026-03-17 · 16 min read #algorithms#data-structures#dynamic-programming#graph-algorithms#coding-interviewAI for Science: AlphaFold, Drug Discovery, Climate AI, and Physics Simulation
A complete guide to AI technologies revolutionizing scientific research — from AlphaFold3 protein structure prediction and molecular GNN drug design to PINN physics simulation and climate prediction AI.
2026-03-17 · 16 min read #aiforscience#alphafold#drugdiscoveryai#pinn#climateaiAI Era Survival Guide Part 8: Survival Strategies for Designers in the Age of Midjourney and Figma AI
In an era where Midjourney, DALL-E, and Stable Diffusion generate images and Figma AI automates design, this guide outlines survival strategies for designers and the design competencies that become even more valuable in
2026-03-17 · 16 min read #career#designer#ai-tools#ai-era#figmaAI Benchmark Datasets Complete Guide: ImageNet, COCO, GLUE, MMLU, HumanEval
A complete guide to key benchmark datasets for AI model evaluation. Detailed analysis of computer vision (ImageNet, COCO, ADE20K), NLP (GLUE, SuperGLUE, SQuAD, MMLU), code (HumanEval, MBPP), and LLM evaluation (HELM, MT-
2026-03-17 · 25 min read #benchmark#datasets#imagenet#coco#gluePrompt Engineering Complete Guide: From Zero-shot to Advanced Techniques
A complete guide to mastering all prompt engineering techniques. Learn Zero-shot, Few-shot, Chain-of-Thought, Tree of Thoughts, ReAct, Self-Consistency, and system prompt design through practical examples.
2026-03-17 · 32 min read #prompt-engineering#llm#chatgpt#claude#aiLLM Application Development Practical Guide: Mastering ChatGPT API, Claude API, and Gemini API
A practical guide to LLM application development covering ChatGPT API, Claude API, and Gemini API.
2026-03-17 · 22 min read #llm#openai#claude#gemini#apiPyTorch Complete Guide: Zero to Hero — From Tensors to Distributed Training
A comprehensive guide to mastering PyTorch from the basics to advanced techniques. Learn tensor operations, automatic differentiation, CNN/RNN/Transformer implementation, and distributed training with practical examples
2026-03-17 · 21 min read #pytorch#deep-learning#ai#python#neural-networkPython Advanced Techniques for AI/ML: Performance Optimization, Parallel Processing, Memory Management
A comprehensive guide to advanced Python techniques for AI/ML development. Master performance profiling, multiprocessing, async/await, Numba JIT, Cython, memory profiling, and type hints with practical examples.
2026-03-17 · 24 min read #python#advanced#performance#multiprocessing#numbaDeep Learning Model Quantization Complete Guide: Master INT8, INT4, GPTQ, AWQ, GGUF
A comprehensive guide to mastering deep learning model quantization. Understand the principles from FP32 to INT8 and INT4 quantization, and master GPTQ, AWQ, GGUF, bitsandbytes, AutoGPTQ, and llama.cpp through practical
2026-03-17 · 23 min read #quantization#model-compression#gptq#awq#ggufHuggingFace Ecosystem Complete Guide: Master Transformers, Datasets, PEFT, and Accelerate
A complete guide to mastering the entire HuggingFace ecosystem. Learn Transformers, Datasets, Tokenizers, PEFT, Accelerate, Diffusers, and Hub API with hands-on examples.
2026-03-17 · 18 min read #huggingface#transformers#peft#accelerate#nlpGenerative AI Complete Guide: Master GANs, VAEs, and Diffusion Models
A complete guide to mastering the core architectures of generative AI. Understand VAE, GAN, DDPM diffusion models, and Stable Diffusion from the ground up with mathematical derivations and complete PyTorch implementation
2026-03-17 · 22 min read #generative-ai#gan#vae#diffusion-model#stable-diffusionGraph Neural Networks Complete Guide: GCN, GAT, GraphSAGE to Molecular Design
A complete guide to Graph Neural Networks from fundamentals to cutting-edge research. Covers graph theory, GCN, GraphSAGE, GAT, Graph Transformer, molecular design, and social network analysis with PyTorch Geometric impl
2026-03-17 · 23 min read #gnn#graph-neural-network#gcn#gat#pytorch-geometricTabular Data ML Complete Guide: Master XGBoost, LightGBM, CatBoost, and TabNet
A complete guide to achieving top performance on tabular data. Master XGBoost, LightGBM, CatBoost ensembles, feature engineering, hyperparameter optimization, and deep learning-based TabNet with Kaggle-level practical te
2026-03-17 · 18 min read #tabular-ml#xgboost#lightgbm#catboost#gradient-boostingDeep Learning Debugging Complete Guide: From Diagnosing Training Failures to Performance Optimization
A complete guide to systematically diagnosing and resolving deep learning training failures. Covers Loss NaN, vanishing/exploding gradients, overfitting, slow convergence, and out-of-memory errors with real-world code ex
2026-03-17 · 19 min read #deep-learning#debugging#pytorch#training#optimizationEdge AI and On-Device ML Complete Guide: TFLite, ONNX, Core ML, llama.cpp
A complete guide to running AI models on edge devices. Learn hands-on how to deploy optimized AI in mobile and edge environments using TensorFlow Lite, ONNX Runtime, Core ML, MediaPipe, llama.cpp, and Whisper.cpp.
2026-03-17 · 25 min read #edge-ai#on-device-ml#tflite#onnx#core-mlDeep Learning Training Methods Complete Guide: From Optimization to Distributed Training
A comprehensive guide covering all techniques for effectively training deep learning models. Learn gradient descent, optimizers, learning rate scheduling, regularization, batch normalization, transfer learning, fine-tuni
2026-03-17 · 28 min read #deep-learning#training#optimization#regularization#distributed-training