个结果，搜索词为 "autoencoders"
状态：免费试用您将获得的技能: Generative Adversarial Networks (GANs), Generative AI, Autoencoders, Deep Learning, Convolutional Neural Networks, Tensorflow, Unsupervised Learning, Dimensionality Reduction, Model Evaluation
状态：免费试用DeepLearning.AI
您将获得的技能: 生成对抗网络 (GAN), 自动编码器, 张力流, 人工神经网络, 生成模型架构, 卷积神经网络, 生成式人工智能, Transfer Learning, 图像分析, 深度学习
状态：免费DeepLearning.AI
您将获得的技能: Embeddings, Retrieval-Augmented Generation, Large Language Modeling, Semantic Web, Vector Databases, Natural Language Processing
Google Cloud
您将获得的技能: 张力流, 递归神经网络 (RNN), Keras（神经网络库）, 生成模型架构, 模型部署, 人工神经网络, Machine Learning 方法
状态：新您将获得的技能: Retrieval-Augmented Generation, Vector Databases, Agentic systems, AI Workflows, Hugging Face, CrewAI, Embeddings, Transfer Learning
状态：免费试用University of Colorado Boulder
您将获得的技能: Image Analysis, Computer Vision, Autoencoders, Convolutional Neural Networks, Vision Transformer (ViT), Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), Deep Learning, Multimodal Prompts, Artificial Intelligence and Machine Learning (AI/ML), Computer Graphics, Visualization (Computer Graphics), Machine Learning Methods, Model Deployment, Embeddings, Artificial Intelligence, Data Ethics, Data Processing, Applied Machine Learning, Linear Algebra
是什么让您今天来到 Coursera？
状态：免费试用您将获得的技能: 大型语言模型, 生成式人工智能, 性能调整, 应用机器学习, Transfer Learning, 嵌入, 自然语言处理, PyTorch（机器学习库）, 文本挖掘
状态：免费试用IBM
您将获得的技能: 机器学习, Python 程序设计, 检索-增强生成, PySpark, Apache Spark, 无监督学习, Keras（神经网络库）, 计算机视觉, 大型语言模型, 监督学习, 生成模型架构, LLM 申请, 视觉转换器（ViT）, 生成式人工智能, Prompt Engineering, 矢量数据库, Transfer Learning, 数据科学, PyTorch（机器学习库）, Model Evaluation
状态：免费试用您将获得的技能: 机器学习, 网络架构, 自动编码器, 递归神经网络 (RNN), Keras（神经网络库）, 分类与回归树 (CART), 回归分析, Transfer Learning, 自然语言处理, 卷积神经网络, 人工神经网络, Model Evaluation, 应用机器学习, 图像分析, 深度学习
状态：免费试用DeepLearning.AI
您将获得的技能: 生成对抗网络 (GAN), 计算机视觉, 网络架构, 分类算法, 自动编码器, 张力流, 生成式人工智能, 可视化（计算机制图）, Keras（神经网络库）, 分布式计算, 人工神经网络, 卷积神经网络, Transfer Learning, 生成模型架构, 性能调整, 图像分析, 深度学习, Model Evaluation
状态：免费试用您将获得的技能: Generative Adversarial Networks (GANs), Generative Model Architectures, Retrieval-Augmented Generation, Generative AI, Autoencoders, ChatGPT, OpenAI, Deep Learning, Model Evaluation, Vision Transformer (ViT), Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Large Language Modeling, Prompt Engineering, PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Computer Vision, Unsupervised Learning, Natural Language Processing
状态：免费试用Microsoft
您将获得的技能: Generative AI, Microsoft Copilot, Generative Adversarial Networks (GANs), Natural Language Processing, Data Quality, Anomaly Detection, Data Storytelling, Technical Communication, Responsible AI, Data Visualization, Data Ethics, Data-Driven Decision-Making, Interactive Data Visualization, Data Pipelines, Data Cleansing, Data Visualization Software, Data Preprocessing, Data Science, Autoencoders, Critical Thinking
是什么让您今天来到 Coursera？
总之，以下是 10 最受欢迎的 autoencoders 课程
- Introduction Course to Autoencoders, VAEs, and GANs: Simplilearn
- 使用 TensorFlow 进行生成式深度学习: DeepLearning.AI
- Embedding Models: From Architecture to Implementation: DeepLearning.AI
- 编码器-解码器结构: Google Cloud
- Generative AI with Python: Packt
- Computer Vision: University of Colorado Boulder
- 用 Transformer 建立生成式 AI 语言模型: IBM
- IBM 人工智能工程: IBM
- 使用 Keras 的深度学习和神经网络简介: IBM
- TensorFlow：高级技术: DeepLearning.AI
