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：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DeepLearning.AI
您将获得的技能: 卷积神经网络, 数据伦理, 生成式人工智能, 图像质量, 生成对抗网络 (GAN), 人工神经网络, Model Evaluation, 信息隐私, 机器学习, 生成模型架构, 无监督学习, 数据综合, PyTorch（机器学习库）, 图像分析, 深度学习, 负责任的人工智能
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
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
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: 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: Model Evaluation, 概率与统计, 逻辑回归, 数据预处理, 人工神经网络, 回归分析, 张力流, 统计方法, PyTorch（机器学习库）
状态：预览University of Washington
您将获得的技能: 概率分布, 生理学, 数学建模, 监督学习, 递归神经网络 (RNN), 强化学习, Matlab, 机器学习算法, 网络模型, 生物学, 线性代数, 人工神经网络, 计算思维, 统计方法, 微分方程, 计算机科学, 信息架构, 神经学, 生物信息学
状态：免费试用DeepLearning.AI
您将获得的技能: Python 程序设计, 卷积神经网络, 微积分, 监督学习, 递归神经网络 (RNN), 人工神经网络, 应用机器学习, 线性代数, 深度学习
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Transfer Learning, Tensorflow, Artificial Neural Networks, Embeddings, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Image Analysis, Classification Algorithms, Convolutional Neural Networks, Natural Language Processing, Computer Vision, Forecasting, Supervised Learning, Machine Learning Algorithms, Machine Learning, Predictive Analytics, Model Evaluation, Predictive Modeling
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
是什么让您今天来到 Coursera？
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
- 使用 Keras 的深度学习和神经网络简介: IBM
- Foundations of Neural Networks: Johns Hopkins University
- 生成对抗网络 (GAN): DeepLearning.AI
- 自然语言处理: DeepLearning.AI
- Deep Learning: Recurrent Neural Networks with Python: Packt
- Design and Build Custom Neural Networks: Coursera
- 神经网络和 PyTorch 简介: IBM
- 计算神经科学: University of Washington
- 神经网络与深度学习: DeepLearning.AI
