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所在平台: Udemy |
课程主页: https://www.udemy.com/course/deep-learning-nlp-for-sentiment-analysis-translation-2023/
课程评论：没有评论
课程名称：深度学习：情感分析与翻译的自然语言处理 2025 课程概述：情感分析和机器翻译模型每天为数百万人所使用。这些深度学习模型（尤其是变压器模型）在当今各个行业中发挥着重要作用。自2010年代早期以来，随着更高效深度学习模型的出现，情感分析和机器翻译领域的技术水平有了显著提升。在本课程中，我们将带您踏上一段精彩的旅程，通过逐步的方法掌握不同的概念。我们将首先了解如何在自然语言处理的背景下处理文本，然后深入构建自己的模型并将其部署到云端，遵循最佳实践。课程将使用TensorFlow 2（由谷歌开发的世界上最受欢迎的深度学习库）和Huggingface。 您将学习： - TensorFlow基础（张量、模型构建、训练和评估） - 深度学习算法，如递归神经网络、注意力模型、变压器和卷积神经网络 - 使用RNN、变压器和Huggingface变压器（Deberta）进行情感分析 - 使用Word2vec和现代变压器（GPT、BERT、ULmfit、Deberta、T5等）进行迁移学习 - 使用RNN、注意力机制、变压器和Huggingface变压器（T5）进行机器翻译 - 模型部署（ONNX格式、量化、FastAPI、Heroku云服务） 如果您希望在职业生涯中更进一步，此课程将是您的理想选择，我们也非常期待帮助您实现目标！该课程由Neuralearn提供，与Neuralearn的其他课程一样，我们非常重视反馈。您在论坛上的评论和问题将帮助我们改进本课程。请随时在论坛上提出任何问题，我们会尽最大努力在最短时间内回复您。 祝您学习愉快！
Sentiment analysis and machine translation models are used by millions of people every single day. These deep learning models (most notably transformers) power different industries today. With the creation of much more efficient deep learning models, from the early 2010s, we have seen a great improvement in the state of the art in the domains of sentiment analysis and machine translation.In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step approach. We shall start by understanding how to process text in the context of natural language processing, then we would dive into building our own models and deploying them to the cloud while observing best practices. We are going to be using Tensorflow 2 (the world's most popular library for deep learning, built by Google) and HuggingfaceYou will learn:The Basics of Tensorflow (Tensors, Model building, training, and evaluation).Deep Learning algorithms like Recurrent Neural Networks, Attention Models, Transformers, and Convolutional neural networks.Sentiment analysis with RNNs, Transformers, and Huggingface Transformers (Deberta)Transfer learning with Word2vec and modern Transformers (GPT, Bert, ULmfit, Deberta, T5...)Machine translation with RNNs, attention, transformers, and Huggingface Transformers (T5)Model Deployment (Onnx format, Quantization, Fastapi, Heroku Cloud)If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.Enjoy!!!
