#PyImageSearch

Learn what YOLO26 is, run Ultralytics YOLO26 object detection on macOS, and benchmark YOLO26 vs YOLO12 with nearly 30% throughput gains on video.

Learn what YOLOE-26 adds to YOLO26: text, visual, and zero-shot prompting for open-vocabulary object detection, with hands-on Ultralytics examples.

Learn how to auto-label a custom dataset with YOLOE-26 visual prompting, clean pseudo-labels, and fine-tune YOLO26 into a class-specific detector.

Learn how DVC brings data and model versioning to MLOps. Track datasets, checkpoints, and pipelines reliably using Git-friendly workflows.

Learn how to build a fully reproducible multi-stage ML pipeline using DVC, including preprocessing, training, evaluation, and automated reruns.

Fine-tune Gemma 4 with QLoRA on the Bitext dataset to build a memory-efficient customer support model using LoRA adapters and TRL.

Fine-tune Gemma 4 with QLoRA to build a customer support agent that calls tools, handles missing details, and responds to complex requests.

Build DeepSeek‑V3 from scratch: explore MLA, MoE, RoPE, and MTP innovations with hands-on training and implementation insights.

Train DeepSeek-V3 from scratch using the Hugging Face Trainer, build a custom trainer, handle gradient accumulation, and generate text on TinyStories.

Fine-tuning Qwen3 for advanced math reasoning using GRPO: boosting precision, structure, and problem-solving accuracy post-training.

Learn how to self-host Langfuse, connect it to vLLM, and build full LLM observability with traces, tokens, latency, and dashboards — from scratch.

Learn manual tracing, LLM evaluation metrics, scoring, and vLLM health checks using self-hosted Langfuse for observability workflows.

Learn how to train Kimi-K2 using DeepSeek-V3, Mixture-of-Experts, and MuonClip for efficient, scalable open-source LLM development.

Build a semantic cache for LLMs using FastAPI, Redis, and cosine similarity to cut latency and cost with exact-match and semantic cache hits.

Learn how to test, validate, and performance-check ML systems using unit tests, integration tests, load testing, and code quality tools.

Learn how to structure ML projects, manage configs, build clean APIs, and apply real software engineering patterns to production-grade MLOps systems.

Build an agentic AI vision system using SAM 3 and Qwen with iterative segmentation, reasoning loops, and self-correcting outputs.

Learn Multi-Token Prediction in DeepSeek-V3, enabling LLMs to forecast multiple tokens and improve coherence, efficiency, and training speed.

Build DeepSeek‑V3 from scratch: explore MLA, MoE, RoPE, and MTP innovations with hands‑on training and implementation insights.

Build DeepSeek‑V3 from scratch: explore MLA, MoE, RoPE, and MTP innovations with hands‑on training and implementation insights.