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Generative AI with Python and TensorFlow 2, by Joseph Babcock and Raghav Bali This GAN book for Python programmers who want to develop and have some fun using generative models. To help you get the most out of this book, you should be prepared to have basic knowledge of from math and ...
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2. 学习基础知识 掌握基础的自然语言处理(NLP)知识,包括语言模型、词嵌入、序列到序列模型等。 了解常见的生成式语言模型架构,如循环神经网络(RNN)、长短期记忆网络(LSTM)、变压器(Transformer)等。 3. 学习相关工具和框架 熟悉使用Python编程语言及其相关库来实现生成式语言模型,如TensorFlow、PyTorch等。
For each scenario, you’ll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications. By the end of this book, you’ll be well equipped to use the generative AI field and start using C...
The term “AI stack,” as used in this article, is interchangeable with “GenAI” or “generative AI stack.”注意:本文是从生成式 AI 领域的角度来谈及 AI 堆栈的。本文中使用的术语“AI 堆栈”可与“GenAI”或“生成式 AI 堆栈”互换。 The AI stack combines integrated tools, libraries, and ...
Generative AI with ONNX Runtime In the era of AI , the portability of AI models is very important. ONNX Runtime can easily deploy trained models to different devices. Developers do not need to pay attention to the inference framework and use a unifi...
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Generative Adversarial Networks (GANs) have become hugely popular for their abilities to generate both beautiful and realistic images, and language models (e.g. ChatGPT) that are increasingly rising in their use across every sector. These GAN models are arguably the reason AI/Machine Learning have...
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