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推动AI边界的突破
为引领AI未来的学生和专业人士提供行业领先的课程与实用资源。
最受欢迎的课程
Python Programming Fundamentals
Acquire the core Python skills needed to write clear, functional code and begin your programming path.
约 20 小时
No prior programming experience.
LangChain for Production-Ready LLM Applications
Develop and operationalize complex, scalable LLM applications using advanced LangChain features and best practices.
约 32 小时
Python & Basic LangChain
Practical Quantization for Large Language Models
Implement LLM quantization techniques (PTQ, QAT, GPTQ, GGUF) to reduce model size and improve inference speed.
约 15 小时
LLM Fundamentals & Python
Python for LLM Workflows: Tooling and Best Practices
Build and manage LLM applications using Python, LangChain, LlamaIndex, and essential development practices.
约 18 小时
Intermediate Python skills
RLHF: Reinforcement Learning from Human Feedback
Apply Reinforcement Learning from Human Feedback (RLHF) principles and techniques to align large language models.
约 24 小时
Advanced ML & DL knowledge
Getting Started with PyTorch
Build and train fundamental deep learning models using PyTorch's core features like tensors, autograd, and neural network modules.
约 18 小时
Basic Python & ML knowledge
Time Series Analysis and Forecasting
Analyze time-dependent data and build statistical forecasting models like ARIMA and SARIMA.
约 15 小时
Basic Python and Pandas
Data Visualization with Matplotlib and Seaborn
Create insightful and customized plots using Python's essential Matplotlib and Seaborn libraries.
约 12 小时
Basic Python helpful
Introduction to Machine Learning
Understand fundamental machine learning concepts and apply basic algorithms to build simple models.
约 14 小时
Basic Python helpful
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课程、参考资料和工具被全球顶尖高校和行业领先科技公司广泛使用与引用。
最新文章与洞见
Jun 23, 2025
The AI Engagement Index ranks nations by their engagement in technical AI content, offering a fresh perspective on the global AI adoption.
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List for NVIDIA RTX 50 series GPU for running large language models locally. Discover the best LLMs for every card, master quantization, and optimize performance for privacy and speed.
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Discover how AI and machine learning priorities differ across the globe. We analyze our user data to reveal the specific tools, techniques, and challenges that engineers from the US, India, China, Germany, and more are focused on right now.
Jun 16, 2025
Learn how to critically evaluate LLM benchmarks and choose the right model for your specific coding needs with our step-by-step guide.
May 24, 2025
Choosing between PyTorch and TensorFlow? This guide details 5 differences covering API design, graph execution, deployment, and community, helping ML engineers select the optimal framework for their projects.
May 24, 2025
Understand the GGUF file format, its architecture, benefits for LLM inferencing, and its role in local model deployment. This guide offers technical professionals essential knowledge for creating, quantizing, and utilizing GGUF files effectively.
May 23, 2025
Discover 5 Proximal Policy Optimization (PPO) variants designed to elevate your Reinforcement Learning from Human Feedback (RLHF) pipelines. This technical guide explains how these modifications address common PPO limitations, leading to better LLM alignment and performance.
May 22, 2025
Selecting the right database is fundamental for building high-performing RAG applications. This guide explores essential criteria, compares database types (vector-native vs. extended traditional DBs), and provides insights to help developers and ML engineers choose the optimal solution for vector search, scalability, and low-latency retrieval.