神经网络课程
神经网络课程可以帮助您学习架构设计、反向传播、激活函数和优化技术的基础知识。您可以掌握训练模型、调整超参数和评估性能指标的技能。许多课程介绍了 TensorFlow 和 PyTorch 等工具，这些工具支持在图像识别、自然语言处理和预测分析等实际应用中实现神经网络。
热门神经网络课程与认证
状态：免费试用您将获得的技能: PyTorch (Machine Learning Library), Text Mining, Artificial Neural Networks, Natural Language Processing, Deep Learning, Applied Machine Learning, Network Architecture, Time Series Analysis and Forecasting, Machine Learning, Data Processing
状态：免费试用您将获得的技能: Tensorflow, Artificial Neural Networks, Deep Learning, Predictive Modeling, Time Series Analysis and Forecasting, Artificial Intelligence and Machine Learning (AI/ML), Natural Language Processing, Data Analysis, Data Processing
状态：预览DeepLearning.AI
您将获得的技能: Deep Learning, Artificial Neural Networks, Artificial Intelligence, NumPy, Computer Vision, Machine Learning, Supervised Learning, Linear Algebra, Calculus
状态：免费试用Universidades Anáhuac
您将获得的技能: Artificial Neural Networks, Keras (Neural Network Library), Deep Learning, Tensorflow, Image Analysis, Computer Vision, Machine Learning Methods, Natural Language Processing, Artificial Intelligence, Python Programming
状态：免费试用DeepLearning.AI
您将获得的技能: 负责任的人工智能, PyTorch（机器学习库）, 生成式人工智能, 计算机视觉, 无监督学习, 数据伦理, 深度学习, 人工神经网络, 生成模型架构
状态：免费试用您将获得的技能: Generative Model Architectures, Generative AI, OpenAI, Large Language Modeling, Prompt Engineering, Artificial Neural Networks, Deep Learning, Natural Language Processing, Machine Learning Methods
状态：预览DeepLearning.AI
您将获得的技能: Deep Learning, Natural Language Processing, Tensorflow, PyTorch (Machine Learning Library), Generative Model Architectures, Applied Machine Learning, Artificial Neural Networks
状态：免费试用您将获得的技能: Artificial Intelligence and Machine Learning (AI/ML), NumPy, PyTorch (Machine Learning Library), Predictive Modeling, Matplotlib, Development Environment, Pandas (Python Package), Deep Learning, Classification And Regression Tree (CART), Python Programming, Artificial Neural Networks, Data Manipulation, Programming Principles, Tensorflow, Regression Analysis, Machine Learning, Computer Programming, Integrated Development Environments
Coursera
您将获得的技能: PyTorch（机器学习库）, Python 程序设计, 深度学习, 图像分析, 生成模型架构
状态：预览DeepLearning.AI
您将获得的技能: Computer Vision, Keras (Neural Network Library), Image Analysis, Deep Learning, Artificial Neural Networks, Tensorflow, Dimensionality Reduction, Visualization (Computer Graphics), Applied Machine Learning, Network Architecture, Algorithms
状态：预览DeepLearning.AI
您将获得的技能: Deep Learning, Supervised Learning, Artificial Neural Networks, Artificial Intelligence, Computer Vision, Machine Learning, Performance Tuning, Machine Learning Algorithms, Python Programming, NumPy, Linear Algebra, Algorithms
状态：免费试用您将获得的技能: Shiny (R Package), Deep Learning, Image Analysis, PyTorch (Machine Learning Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Classification And Regression Tree (CART), Unsupervised Learning, Predictive Modeling, Regression Analysis, Dimensionality Reduction, Network Architecture, Interactive Data Visualization, Time Series Analysis and Forecasting, Data Processing
与 neural networks 相关的搜索
总之，以下是 10 最受欢迎的 neural networks 课程
- RNN Architecture and Sentiment Classification: Packt
- Advanced RNN Concepts and Projects: Packt
- Neuronale Netze und Deep Learning: DeepLearning.AI
- Deep Learning: Del Concepto a la Práctica: Universidades Anáhuac
- 构建基本的生成对抗网络 (GAN): DeepLearning.AI
- Attention Mechanisms and Transformer Models Course: Simplilearn
- Последовательные модели: DeepLearning.AI
- Fundamentals of AI, Machine Learning, and Python Programming: Packt
- 使用 PyTorch 进行深度学习：生成对抗网络: Coursera
- Réseaux neuronaux convolutifs: DeepLearning.AI
