个结果，搜索词为 "artificial neural network"
状态：免费试用您将获得的技能: Model Evaluation, 回归分析, 概率与统计, PyTorch（机器学习库）, 逻辑回归, 数据预处理, 人工神经网络, 张力流, 模型评估, 统计方法
状态：免费试用您将获得的技能: 深度学习, Model Evaluation, 回归分析, 网络架构, 卷积神经网络, 递归神经网络 (RNN), 自然语言处理, Keras（神经网络库）, 迁移学习, 机器学习, 人工神经网络, Transfer Learning, 生成模型架构, 模型评估, 分类与回归树 (CART), 图像分析
状态：新状态：预览您将获得的技能: Exploratory Data Analysis, Feature Engineering, Data Analysis, Data Preprocessing, Model Evaluation, Data Cleansing, Data Transformation, Predictive Modeling, Pandas (Python Package), Applied Machine Learning, Statistical Methods, Regression Analysis, Scikit Learn (Machine Learning Library), Artificial Neural Networks
状态：免费试用DeepLearning.AI
您将获得的技能: 深度学习, 递归神经网络 (RNN), 卷积神经网络, 人工神经网络, 线性代数, 微积分, Python 编程, 监督学习, 应用机器学习
状态：新状态：免费试用您将获得的技能: Keras (Neural Network Library), Tensorflow, Artificial Neural Networks, Deep Learning, Data Preprocessing, Model Evaluation, Customer Analysis, Applied Machine Learning, Scikit Learn (Machine Learning Library), Development Environment, Predictive Analytics, Pandas (Python Package), Data Cleansing
状态：免费试用CertNexus
您将获得的技能: 深度学习, 计算机视觉, 卷积神经网络, 预测建模, 人工智能和机器学习（AI/ML）, 决策树学习, 机器学习算法, 递归神经网络 (RNN), 自然语言处理, 人工神经网络, 分类算法, 随机森林算法, 监督学习, 应用机器学习
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: 深度学习, Model Evaluation, 机器学习方法, 数据预处理, 人工神经网络, 张力流, 模型评估, 性能调整, 验证和确认
状态：预览Sungkyunkwan University
您将获得的技能: Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Image Analysis, Computer Vision, Artificial Neural Networks, Natural Language Processing, Deep Learning, Machine Learning
状态：新状态：免费试用您将获得的技能: Model Evaluation, Keras (Neural Network Library), Technical Documentation, Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Data Analysis, Applied Machine Learning, Network Architecture, Supervised Learning
状态：新状态：预览您将获得的技能: Generative AI, Recurrent Neural Networks (RNNs), Tensorflow, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Machine Learning
状态：新状态：免费试用您将获得的技能: Computer Vision, Image Analysis, Model Evaluation, Convolutional Neural Networks, Artificial Neural Networks, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Applied Machine Learning, Embeddings, Network Architecture, Transfer Learning, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, NumPy, Python Programming, Matplotlib, Data Visualization, Data Science
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
总之，以下是 10 最受欢迎的 artificial neural network 课程
- 神经网络和 PyTorch 简介: IBM
- 使用 Keras 的深度学习和神经网络简介: IBM
- Apply Neural Networks for Car Price Prediction: EDUCBA
- 神经网络与深度学习: DeepLearning.AI
- Deep Learning with ANN in Python: Build & Optimize: EDUCBA
- 构建决策树、SVM 和人工神经网络: CertNexus
- 改进深度神经网络：超参数调整、正则化和优化: DeepLearning.AI
- Fundamentals of CNNs and RNNs: Sungkyunkwan University
- Start Neural Networks Advanced Model Architectures: Coursera
- Become AI-Ready: Deep Learning Fundamentals: LearnKartS
