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探索神经网络课程目录
状态：免费试用DeepLearning.AI
您将获得的技能: 监督学习, 人工神经网络, 深度学习, 计算机视觉, Python 程序设计, 机器学习, 微积分, 线性代数, 人工智能
状态：免费试用您将获得的技能: 计算机视觉, 网络架构, 深度学习, 人工神经网络, 网络模型, 回归分析, 张力流, Keras（神经网络库）, 机器学习, Machine Learning 方法, 自然语言处理, 图像分析
状态：新状态：免费试用Pearson
您将获得的技能: Large Language Modeling, Deep Learning, Prompt Engineering, Image Analysis, PyTorch (Machine Learning Library), Tensorflow, LLM Application, Computer Vision, Responsible AI, Natural Language Processing, Generative AI, Artificial Neural Networks, Data Ethics, Multimodal Prompts, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Methods, Artificial Intelligence, Application Deployment, Time Series Analysis and Forecasting
状态：新状态：免费试用您将获得的技能: Tensorflow, Artificial Neural Networks, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Image Analysis, Natural Language Processing, Computer Vision, Forecasting, Classification And Regression Tree (CART), Supervised Learning, Machine Learning, Text Mining, Predictive Analytics, NumPy, Network Architecture, Data Processing, Data Science
状态：新状态：预览您将获得的技能: Data Visualization Software, R Programming, Scatter Plots, Regression Analysis, Statistical Programming, Predictive Modeling, Artificial Neural Networks, Data Science, Deep Learning, Descriptive Statistics, Predictive Analytics, Statistical Methods, Data Manipulation, Performance Testing, Data Cleansing
状态：免费试用Johns Hopkins University
您将获得的技能: Responsible AI, Data Ethics, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Reinforcement Learning, Generative AI, Debugging, Artificial Intelligence, Unsupervised Learning, Machine Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Applied Machine Learning, Bayesian Statistics, Network Architecture, Linear Algebra, Markov Model
是什么让您今天来到 Coursera？
状态：免费试用DeepLearning.AI
您将获得的技能: 调试, MLOps（机器学习 Operator）, 人工智能和机器学习（AI/ML）, 自然语言处理, 数据驱动的决策制定, 文本挖掘, 机器学习算法, 计算机视觉, Python 程序设计, 深度学习, 机器学习, 人工神经网络, 应用机器学习, 线性代数, 人工智能, 张力流, PyTorch（机器学习库）, 性能调整, 监督学习, 图像分析
状态：免费试用您将获得的技能: 数据操作, 深度学习, 人工神经网络, 回归分析, 机器学习, PyTorch（机器学习库）, 预测建模, 张力流, 概率与统计
状态：免费试用Johns Hopkins University
您将获得的技能: Artificial Neural Networks, Machine Learning Algorithms, Deep Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Network Architecture, Linear Algebra, Performance Tuning, Probability & Statistics
状态：免费试用DeepLearning.AI
您将获得的技能: 数据处理, 深度学习, 人工智能和机器学习（AI/ML）, 计算机视觉, 人工神经网络, 张力流, 应用机器学习, Algorithm, 图像分析
状态：免费试用DeepLearning.AI
您将获得的技能: 机器学习算法, 网络架构, 人工神经网络, 深度学习, 分析, 机器学习, 人工智能, 应用机器学习, 性能调整, Algorithm, 张力流
状态：免费试用您将获得的技能: PyTorch (Machine Learning Library), Tensorflow, Artificial Intelligence, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Application Deployment, Text Mining, Machine Learning, Natural Language Processing, Predictive Modeling, Python Programming, Time Series Analysis and Forecasting, Artificial Intelligence and Machine Learning (AI/ML), Network Architecture, Performance Tuning, Data Science, Data Processing, Data Analysis
Neural Networks 学习者也搜索
总之，以下是 10 最受欢迎的 neural networks 课程
- 神经网络与深度学习: DeepLearning.AI
- 使用 Keras 的深度学习和神经网络简介: IBM
- Learning Deep Learning: Pearson
- Deep Learning with TensorFlow: Packt
- Deep Learning with R: Build & Predict Neural Networks: EDUCBA
- Foundations of Neural Networks: Johns Hopkins University
- 深度学习: DeepLearning.AI
- 神经网络和 PyTorch 简介: IBM
- Introduction to Neural Networks: Johns Hopkins University
- 卷积神经网络: DeepLearning.AI
