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Explore the evolution of Convolutional Neural Networks from the 1980s to present day, highlighting key breakthroughs and advancements in this fundamental deep learning architecture.
Master local implementation of Mono-InternVL for advanced computer vision tasks including OCR, object detection, and image parsing using Python, achieving high-precision results.
Master building a Deep Search Agent like ChatGPT with Python - complete architecture, code implementation, and chatbot integration in this hands-on tutorial.
Explore GRPO training experiments on small Gemma language models with practical implementations and hands-on demonstrations in this focused machine learning tutorial.
Master LangGraph framework fundamentals and build AI agents from scratch, including advanced design patterns and a complete DeepSearch ReAct Agent project.
Learn to build a Python application that enables interactive video conversations using Vision Language Models and Computer Vision techniques for local video Q&A functionality.
Learn how to fine-tune and run SmolVLM2, the smallest video language model designed for edge devices like iPhones, with step-by-step instructions.
Master fine-tuning LLMs for reasoning tasks using GRPO and Unsloth library, requiring only 7GB VRAM. Learn environment setup, data preparation, model training, and result analysis for local implementation.
Discover essential Python coding techniques for machine learning across four key areas: vectorization, comprehension, built-in functions, and generators & iterators to optimize your ML code.
Explore Mistral's new OCR model capabilities through rigorous testing on challenging tasks to evaluate its performance and practical applications.
Explore AI-powered rap generation using Tacotron 2 and ChatGPT. Learn to create a user-friendly interface with Gradio for generating lyrics and vocals.
Use Grad-CAM and Guided Grad-CAM to interpret neural-network predictions for real and fake face images.
Explore a graphical solver for mathematical optimization, visualizing function minimization with equality constraints and generating LLM-based reports for enhanced understanding.
Discover how to build a RAG pipeline using LLaMA 3.1 to automate article discovery and summarization based on Google Trends, showcased in a Streamlit web app for efficient content curation.
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