Recurrent Neural Network 课程
Recurrent Neural Network（循环神经网络）课程可以帮助您学习序列预测、时间序列分析和自然语言处理技术。您可以掌握设计和训练 RNN Architecture、优化模型性能和实施长短期记忆（LSTM）网络的技能。许多课程介绍了 TensorFlow 和 Keras 等工具，这些工具支持开发需要处理序列数据的 AI 应用程序，使您能够在实际场景中应用所学知识。
热门递归神经网络课程和认证
状态：免费试用Johns Hopkins University
您将获得的技能: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Supervised Learning, Artificial Neural Networks, Model Evaluation, Decision Tree Learning, Network Planning And Design, Machine Learning, Computer Vision
University of Colorado Boulder
您将获得的技能: Large Language Modeling, Recurrent Neural Networks (RNNs), Natural Language Processing, Prompt Engineering, Artificial Neural Networks, Transfer Learning, Deep Learning, PyTorch (Machine Learning Library), Embeddings, Model Evaluation, Network Architecture
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Artificial Neural Networks, Deep Learning, Matplotlib, Convolutional Neural Networks, Linear Algebra, Image Analysis, Data Visualization, NumPy, Machine Learning Algorithms, Keras (Neural Network Library), Pandas (Python Package), Seaborn, Artificial Intelligence and Machine Learning (AI/ML), Data Science, Applied Machine Learning, Tensorflow, Data Analysis, Artificial Intelligence, Machine Learning
您将获得的技能: Data Preprocessing, Deep Learning, Artificial Neural Networks, Logistic Regression, Data Cleansing, Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Model Evaluation, Network Architecture, Machine Learning Algorithms, NumPy, Pandas (Python Package), Performance Tuning
状态：免费试用您将获得的技能: Generative Adversarial Networks (GANs), Exploratory Data Analysis, Model Deployment, Keras (Neural Network Library), NumPy, Transfer Learning, PyTorch (Machine Learning Library), Predictive Modeling, Matplotlib, Data Analysis, Artificial Intelligence, Data Preprocessing, Development Environment, Pandas (Python Package), Deep Learning, Classification And Regression Tree (CART), Artificial Neural Networks, Image Analysis, Machine Learning, Data Science
状态：免费试用DeepLearning.AI
您将获得的技能: 模型评估, 张力流, 深度学习, 分类算法, 迁移学习, 卷积神经网络, 机器学习, 应用机器学习, 数据预处理, Keras（神经网络库）, 计算机视觉, 图像分析
状态：免费试用DeepLearning.AI
您将获得的技能: 张力流, 深度学习, 自然语言处理, 人工神经网络, 文本挖掘, 递归神经网络 (RNN), 嵌入, 应用机器学习
状态：新状态：预览您将获得的技能: Plot (Graphics), Data Visualization Software, R Programming, Scatter Plots, Regression Analysis, Statistical Modeling, Predictive Modeling, Artificial Neural Networks, Data Science, Deep Learning, Model Evaluation, Descriptive Statistics, Predictive Analytics, Statistical Methods, Data Manipulation, Data Preprocessing, Performance Testing
状态：免费试用您将获得的技能: 张力流, 自动编码器, Machine Learning 方法, 模型评估, 生成对抗网络 (GAN), 生成式人工智能, 深度学习, 强化学习, 卷积神经网络, 人工神经网络, 递归神经网络 (RNN), 性能调整, 无监督学习, 计算机视觉, 人工智能和机器学习（AI/ML）, Keras（神经网络库）, 迁移学习
状态：免费试用DeepLearning.AI
您将获得的技能: 模型评估, PyTorch（机器学习库）, 嵌入, 应用机器学习, 自然语言处理, 递归神经网络 (RNN), Keras（神经网络库）, 迁移学习
状态：预览DeepLearning.AI
您将获得的技能: Recurrent Neural Networks (RNNs), Deep Learning, Natural Language Processing, Tensorflow, PyTorch (Machine Learning Library), Generative Model Architectures, Applied Machine Learning, Artificial Neural Networks, Embeddings
状态：预览University of Glasgow
您将获得的技能: 人工智能, 负责任的人工智能, 自然语言处理, 模型评估, 生成式人工智能, 大型语言模型, ChatGPT, 深度学习, 人工神经网络, LLM 申请, OpenAI, 数据伦理
总之，以下是 10 最受欢迎的 recurrent neural network 课程
- Mastering Neural Networks and Model Regularization: Johns Hopkins University
- Deep Learning for Natural Language Processing: University of Colorado Boulder
- Deep Learning with Real-World Projects: Packt
- Deep Neural Network for Beginners Using Python: Packt
- Keras Deep Learning & Generative Adversarial Networks (GAN): Packt
- TensorFlow 中的卷积神经网络: DeepLearning.AI
- 利用序列模型进行自然语言处理: DeepLearning.AI
- Deep Learning with R: Build & Predict Neural Networks: EDUCBA
- 使用 Keras 和 TensorFlow 进行深度学习: IBM
- 利用注意力模型进行自然语言处理: DeepLearning.AI
