京东 11.11 红包
Two Sigma Presents_ Machine Learning Models of Financial Data
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FinRL Reinforcement Learning in Finance
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TGN Temporal Graph Networks for Deep Learning on Dynamic Graphs [Paper Explained
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什么是meta learning: 如何用ChatGPT 学习新的机器学习概念（meta learning, 元学习）
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GNN paper reading: 图网络跟对比学习结合应用到推荐系统业务场景
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Advance CUDA编程基础 (C++ programming)
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Stanford CS224W Machine Learning Graphs I 2023 I Knowledge Graph Embeddings
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PPO算法 - Deep Reinforcement Learning
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The Modern Stack for ML Infrastructure _ Outerbounds
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A Theory of Appropriateness with Applications to Generative Artificial Intellige
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Day 2 Breakout Session: 分布式训练 PyTorch XLA FSDP
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Financial Engineering Playground Signal Processing, Robust Estimation, Kalman,
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Python Iterators! COPY or NO COPY_
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Jacob Andreas What Learning Algorithm is In-Context Learning
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Monte Carlo Simulation for Option Pricing with Python (Basic Ideas Explained)
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AI 产品介绍(imagica.ai)：无需代码就可以制作AI 应用
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Pragmatic AI with TypeChat Daniel Rosenwasser
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Quant Magazine: 2023's 物理学最大的进展
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联邦学习：Federated Learning on Decentralized Data (Google I_O'19)
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雅虎新闻：2024年生成式AI的看点
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Jacob Andreas - Good Old-fashioned LLMs (or, Autoformalizing the World)
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Two Sigma Presents Deep Learning for Sequences in Quantitative Finance David Kri
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Lecture 17 - TinyEngine - Efficient Training and Inference on Microcontrollers _
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半导体的现在与未来(台积电)： Semiconductor Industry Present&Future(Kevin_Zhang)
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What's next for AI agentic workflows ft. Andrew Ng of AI Fund
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google deepmind 首席科学家访谈
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Lecture 15 - On-Device Training and Transfer Learning (Part I) _ MIT 6.S965
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如何fine-tune 大语言模型：IntuitiveAI-Finetuning
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Fine-tune Mixtral 8x7B (MoE) on Custom Data - Step by Step Guide
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大语言模型开发工具： Pydantic is all you need - JasonLiu
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【中英双语】ChatGPT背后的数学原理是什么？带你看懂Transformer模型的数学矩阵实现！
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Coding Online Softmax in PyTorch - a faster Softmax via reduced memory access
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Y2Mate.is - Lecture 19 - Efficient Video Understanding and Generative Models MI
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LCM-LoRA, S-LoRA, LoRAX 讲解（英文，b站自动翻译中文字幕）
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怪不得都说Github是学Python人的天堂!!!
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What's next for photonics-powered data centers and AI
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Tutorial: Neural Algorithmic Reasoning
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MIT 演讲：Ilya Sutskever_解释元学习和RL
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运龙的毕业答辩 - Learning Robot Control From RL to Differential Simulation
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Notion AI - NLP 大语言模型里面的embedding layer
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大语言模型-Prompt Engineering (LLM Bootcamp)