08
Nov
Building an OpenAI API Service with FastAPI
A practical guide to building an enterprise-grade OpenAI API microservice in FastAPI featuring rate limiting, fallback routing, and token cost logging.
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08
Nov
Document Intelligence with Python OCR + LLM Extraction
A practical architecture for document intelligence in Python: OCR, field extraction with LLMs, confidence scores, and human review queues.
08
Nov
Hire a Python AI Developer in India: Skills Checklist
A practical skills checklist for hiring a Python AI developer in India: FastAPI, RAG, LLM APIs, hybrid Laravel architecture, and production habits.
08
Nov
Observability for Python LLM Services: Logs, Tokens, Traces
How to observe Python LLM services in production: structured logs, token cost tracking, traces, and quality signals beyond uptime checks.
08
Nov
Python AI Developer Roadmap for Full-Stack Engineers
A step-by-step career transition roadmap for web developers moving into Python AI engineering — from LLM APIs to RAG, Vector DBs, and Agentic frameworks.
08
Nov
Accelerating AI Models with ONNX Runtime and TensorRT in Python Services
A practical, 1,500+ word engineering guide to accelerating AI model inference speed using ONNX Runtime and NVIDIA TensorRT in Python web services — covering model export, graph optimization, FP16/INT8 precision, and C++ engine execution.
08
Nov
Computer Vision in Python: OpenCV, PyTorch Vision, and Image Intelligence Pipelines
A practical, 1,500+ word engineering guide to computer vision pipelines in Python — combining OpenCV image processing, torchvision neural networks, object detection (YOLO), and web API integration.
08
Nov
Deploying PyTorch and Hugging Face Models inside FastAPI Backends
A practical, 1,500+ word engineering guide to serving PyTorch and Hugging Face models inside FastAPI microservices — async request handling, lifespan context startup, batch processing, GPU concurrency, and Docker packaging.
08
Nov
Fine-Tuning Llama & Mistral Models with PyTorch and PEFT/LoRA
A practical, 1,500+ word engineering guide to fine-tuning open-source LLMs using PyTorch, Hugging Face PEFT, and LoRA (Low-Rank Adaptation) — parameter-efficient training, dataset formatting, QLoRA 4-bit setup, and model merging.
08
Nov
Hugging Face Transformers in Python: Loading Open-Source LLMs and Embeddings
A practical, 1,500+ word engineering tutorial for Python developers using Hugging Face Transformers — loading open-source LLMs, computing text embeddings, quantization with bitsandbytes, and pipeline optimization.
08
Nov
PyTorch for Web Engineers: Fine-Tuning, Model Loading, and Production Inference
A practical, 1,500+ word engineering guide for web developers learning PyTorch — covering model loading, GPU memory management, dataset loaders, fine-tuning loops, and serving via web APIs.
08
Nov
PyTorch vs TensorFlow in 2026: Which Framework Should Backend Engineers Learn?
A comprehensive, 1,600+ word technical comparison of PyTorch and TensorFlow for backend engineers and software architects — covering graph execution paradigms, debugging experience, production serving, Hugging Face ecosystem, and career positioning in 2026.
Showing 1 to 12 of 15 articles