个结果，搜索词为 "recurrent neural networks (rnns)"
状态：新状态：免费试用您将获得的技能: Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Keras (Neural Network Library), Image Analysis, Deep Learning, Tensorflow, Computer Vision, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Data Manipulation, Data Transformation, Financial Forecasting, Data Visualization, Time Series Analysis and Forecasting, Exploratory Data Analysis, Python Programming, Customer Analysis, Applied Machine Learning, Cloud Computing
状态：免费试用Johns Hopkins University
您将获得的技能: Responsible AI, Autoencoders, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Debugging, Artificial Intelligence, Image Analysis, Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Computer Vision
状态：免费试用您将获得的技能: Model Deployment, PyTorch (Machine Learning Library), Recurrent Neural Networks (RNNs), Tensorflow, Artificial Intelligence, Applied Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Text Mining, Machine Learning, Natural Language Processing, Deep Learning, Predictive Modeling, Classification Algorithms, Supervised Learning, Time Series Analysis and Forecasting, Network Architecture, Data Science, Model Evaluation
状态：新状态：免费试用您将获得的技能: Network Architecture, Artificial Neural Networks, Network Planning And Design, Performance Testing, Deep Learning
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Embeddings, Time Series Analysis and Forecasting, Tensorflow, Natural Language Processing, Forecasting, Image Analysis, Deep Learning, Artificial Neural Networks, Predictive Analytics, Predictive Modeling, Technical Analysis, Data Preprocessing, Supervised Learning, Data Science, Machine Learning
状态：免费试用DeepLearning.AI
您将获得的技能: Algorithm, 监督学习, Machine Learning 方法, 嵌入, 深度学习, Keras（神经网络库）, 递归神经网络 (RNN), 功能工程, 马尔可夫模型, 降维, 数据预处理, 统计机器学习, 人工神经网络, 张力流, 自然语言处理, Transfer Learning, 应用机器学习, 分类算法, PyTorch（机器学习库）, 文本挖掘
是什么让您今天来到 Coursera？
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Transfer Learning, Convolutional Neural Networks, Deep Learning, Keras (Neural Network Library), Tensorflow, Artificial Neural Networks, PyTorch (Machine Learning Library), Image Analysis, Natural Language Processing, Computer Vision, Model Evaluation, Data Preprocessing
状态：新状态：预览您将获得的技能: Artificial Intelligence and Machine Learning (AI/ML)
状态：预览Sungkyunkwan University
您将获得的技能: Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Image Analysis, Artificial Neural Networks, Computer Vision, Deep Learning, Network Architecture, Machine Learning
状态：免费试用您将获得的技能: 卷积神经网络, 自动编码器, Keras（神经网络库）, 递归神经网络 (RNN), 回归分析, Model Evaluation, 分类与回归树 (CART), Transfer Learning, 人工神经网络, 自然语言处理, 机器学习, 应用机器学习, 网络架构, 图像分析, 深度学习
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Transfer Learning, Natural Language Processing, Deep Learning, PyTorch (Machine Learning Library), Large Language Modeling, Keras (Neural Network Library), Artificial Neural Networks, Image Analysis, Tensorflow, Artificial Intelligence, Machine Learning Methods, Computer Vision, Embeddings, Data Preprocessing, Model Evaluation
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Transfer Learning, Large Language Modeling, Natural Language Processing, Vision Transformer (ViT), Deep Learning, PyTorch (Machine Learning Library), Tensorflow, Artificial Neural Networks, Embeddings, Computer Vision
总之，以下是 10 最受欢迎的 recurrent neural networks (rnns) 课程
- Deep Learning with Python: CNN, ANN & RNN: EDUCBA
- Foundations of Neural Networks: Johns Hopkins University
- Deep Learning: Recurrent Neural Networks with Python: Packt
- Design and Build Custom Neural Networks: Coursera
- Deep Learning - Recurrent Neural Networks with TensorFlow: Packt
- 自然语言处理: DeepLearning.AI
- Deep Learning & Modern AI Architectures: Packt
- Analyze and Build Deep Learning Models with TensorFlow: EDUCBA
- Fundamentals of CNNs and RNNs: Sungkyunkwan University
- 使用 Keras 的深度学习和神经网络简介: IBM
