个结果，搜索词为 "artificial neural network"
您将获得的技能: 人工神经网络, 预测建模, 数据处理, PyTorch（机器学习库）, 模型培训, Model Evaluation, 模型评估, 回归分析, 概率与统计, 逻辑回归, 张力流, 模型优化, 应用机器学习, 统计方法
IBM
您将获得的技能: 风险缓解, 负责任的人工智能, 法学硕士申请, 生成模型架构, 生成式人工智能, 自然语言处理, 人工智能扫盲, 机器人
您将获得的技能: Transfer Learning, 自动编码器, 机器学习, 卷积神经网络, 网络架构, 人工神经网络, 递归神经网络 (RNN), Keras（神经网络库）, 图像分析, 自然语言处理, 模型培训, 迁移学习, 机器学习方法, 回归分析, 深度学习, 应用机器学习, 模型优化
您将获得的技能: Computer Vision, Image Analysis, Model Evaluation, Convolutional Neural Networks, Model Optimization, Artificial Neural Networks, Model Training, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Transfer Learning, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, NumPy, Python Programming, Matplotlib, Data Visualization, Data Science
DeepLearning.AI
您将获得的技能: 卷积神经网络, 递归神经网络 (RNN), 人工神经网络, 监督学习, 人工智能, 模型培训, 机器学习方法, 深度学习, 模型优化, Python 编程, 应用机器学习
CertNexus
您将获得的技能: 决策树学习, 预测建模, 人工智能和机器学习（AI/ML）, 卷积神经网络, 人工神经网络, 递归神经网络 (RNN), 分类算法, 监督学习, 分类与回归树 (CART), 计算机视觉, 自然语言处理, 模型培训, 机器学习算法, 深度学习, 随机森林算法, 应用机器学习
是什么让您今天来到 Coursera？
您将获得的技能: Keras (Neural Network Library), Tensorflow, Artificial Neural Networks, Deep Learning, Model Training, Data Preprocessing, Model Optimization, Model Evaluation, Data Processing, Development Environment, Predictive Analytics, Software Installation
DeepLearning.AI
您将获得的技能: 人工智能和机器学习（AI/ML）, 人工神经网络, 性能调整, 验证和确认, 模型培训, 机器学习方法, Model Evaluation, 模型评估, 深度学习, 张力流, 应用机器学习, 调试, 模型优化
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, Applied Machine Learning, Deep Learning, Machine Learning
您将获得的技能: Generative AI, Generative Model Architectures, Generative Adversarial Networks (GANs), Computer Vision, Image Analysis, Model Evaluation, Convolutional Neural Networks, Autoencoders, Model Optimization, Vision Transformer (ViT), Artificial Neural Networks, Model Deployment, Model Training, Deep Learning, Recurrent Neural Networks (RNNs), Embeddings, Machine Learning Methods, PyTorch (Machine Learning Library), AI Enablement, Artificial Intelligence
Johns Hopkins University
您将获得的技能: Responsible AI, Autoencoders, Model Training, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Model Optimization, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Debugging, Machine Learning Methods, Artificial Intelligence, Image Analysis, Unsupervised Learning, Bayesian Network
您将获得的技能: Model Evaluation, Keras (Neural Network Library), Software Documentation, Technical Documentation, Artificial Neural Networks, PyTorch (Machine Learning Library), Model Training, Deep Learning, Model Optimization, Applied Machine Learning, Network Architecture
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
- 人工智能（AI）简介: IBM
- 使用 Keras 的深度学习和神经网络简介: IBM
- Neural Networks and Computer Vision Foundations: Edureka
- 神经网络与深度学习: DeepLearning.AI
- 构建决策树、SVM 和人工神经网络: CertNexus
- Deep Learning with ANN in Python: Build & Optimize: EDUCBA
- 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
- Advanced Deep Learning Architectures: Edureka
