神经网络
神经元网络知识库可以帮助您了解如何建立、训练和优化模型。您可以在建筑设计、数据挖掘、培训技术和模型评估等方面有所建树。许多课程都有 KI-Praxis 框架和要点。
令人信服的神经网络工具和证书
状态：新状态：免费试用Dartmouth College
您将获得的技能: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Classification Algorithms, Statistical Inference
状态：免费试用DeepLearning.AI
您将获得的技能: 卷积神经网络, 监督学习, 人工神经网络, 深度学习, Python 程序设计, 应用机器学习, 递归神经网络 (RNN), 线性代数, 微积分
状态：免费试用您将获得的技能: 卷积神经网络, 深度学习, Keras（神经网络库）, 递归神经网络 (RNN), 分类与回归树 (CART), 机器学习, 迁移学习, 自然语言处理, 人工神经网络, 图像分析, 模型评估, 网络架构, 回归分析
状态：免费试用DeepLearning.AI
您将获得的技能: PyTorch（机器学习库）, 卷积神经网络, 深度学习, 人工智能和机器学习（AI/ML）, 数据预处理, 监督学习, 人工神经网络, 机器学习, 张力流, 嵌入, 应用机器学习, Keras（神经网络库）, 递归神经网络 (RNN), 迁移学习, 拥抱的脸, 性能调整, 图像分析, 调试, 自然语言处理, 计算机视觉
状态：免费试用您将获得的技能: 概率与统计, 深度学习, PyTorch（机器学习库）, 数据预处理, 分类算法, 人工神经网络, Machine Learning 方法, 预测建模, 回归分析, 张力流, 逻辑回归, 模型评估
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
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: 卷积神经网络, PyTorch（机器学习库）, 深度学习, 数据预处理, 人工神经网络, Keras（神经网络库）, 迁移学习, 计算机视觉, 张力流, 图像分析
状态：免费试用您将获得的技能: PyTorch（机器学习库）, 深度学习, 卷积神经网络, 分类算法, 人工智能和机器学习（AI/ML）, Machine Learning 方法, 监督学习, 人工神经网络, 应用机器学习, 模型评估, 逻辑回归
状态：免费试用DeepLearning.AI
您将获得的技能: Machine Learning 方法, 数据预处理, 深度学习, 人工神经网络, 验证和确认, 模型评估, 性能调整, 张力流
状态：免费试用Johns Hopkins University
您将获得的技能: Autoencoders, Recurrent Neural Networks (RNNs), Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Data Ethics, Markov Model
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
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
是什么让您今天来到 Coursera？
总之，以下是 10 最受欢迎的 neural network 课程
- Practical Machine Learning: Foundations to Neural Networks: Dartmouth College
- 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
- 深度学习: DeepLearning.AI
- 神经网络和 PyTorch 简介: IBM
- Foundations of Neural Networks: Johns Hopkins University
- 卷积神经网络: DeepLearning.AI
- 使用 PyTorch 进行深度学习: IBM
- 改进深度神经网络：超参数调整、正则化和优化: DeepLearning.AI
- Advanced Neural Network Techniques: Johns Hopkins University
