卷积神经网络课程
卷积神经网络课程可以帮助您学习图像分类、Object Detection 和 Feature Extraction 技术。您可以掌握优化神经网络 Architecture、实施数据 Augmentation 策略以及针对特定任务对模型进行微调的技能。许多课程介绍了 TensorFlow 和 Keras 等工具，这些工具支持构建和训练 CNN，以及评估模型性能和部署计算机视觉和 AI 驱动解决方案等领域应用的方法。
热门卷积神经网络课程和认证
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Tensorflow, Transfer Learning, Natural Language Processing, Embeddings, Image Analysis, Deep Learning, Computer Vision, Time Series Analysis and Forecasting
状态：免费试用您将获得的技能: Generative Adversarial Networks (GANs), Generative AI, Autoencoders, Deep Learning, Convolutional Neural Networks, Tensorflow, Unsupervised Learning, Dimensionality Reduction, Model Evaluation
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, 负责任的人工智能, 数据伦理, 无监督学习, 生成模型架构, 生成对抗网络 (GAN), 深度学习, 人工神经网络, 图像分析
状态：新状态：免费试用您将获得的技能: Keras (Neural Network Library), Convolutional Neural Networks, Transfer Learning, Model Evaluation, Image Analysis, Computer Vision, Deep Learning, Tensorflow, Applied Machine Learning, Data Preprocessing, Jupyter, Matplotlib, Visualization (Computer Graphics)
状态：新状态：免费试用您将获得的技能: Convolutional Neural Networks, Tensorflow, Deep Learning, Transfer Learning, Artificial Neural Networks, Image Analysis, Computer Vision, Applied Machine Learning, Classification Algorithms, Model Deployment, Data Preprocessing, Network Architecture, Model Evaluation
状态：预览Simplilearn
您将获得的技能: Autoencoders, Generative AI, Embeddings, Generative Model Architectures, Prompt Engineering, Image Analysis, Unsupervised Learning, PyTorch (Machine Learning Library), Transfer Learning
状态：免费试用Johns Hopkins University
您将获得的技能: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Supervised Learning, Artificial Neural Networks, Model Evaluation, Decision Tree Learning, Network Planning And Design, Machine Learning, Computer Vision
状态：预览Universidad de los Andes
您将获得的技能: Recurrent Neural Networks (RNNs), Deep Learning, Convolutional Neural Networks, Generative Model Architectures, Generative Adversarial Networks (GANs), Transfer Learning, Vision Transformer (ViT), Image Analysis, Artificial Neural Networks, Machine Learning Methods, Computer Vision, Network Architecture, Natural Language Processing
状态：免费试用DeepLearning.AI
您将获得的技能: PyTorch（机器学习库）, 自然语言处理, 模型评估, 迁移学习, Keras（神经网络库）, 应用机器学习, 嵌入, 递归神经网络 (RNN)
状态：新状态：免费试用您将获得的技能: Deep Learning, Convolutional Neural Networks, PyTorch (Machine Learning Library), Recurrent Neural Networks (RNNs), Keras (Neural Network Library), Artificial Neural Networks, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Transfer Learning, Tensorflow, Python Programming, Data Preprocessing, Network Architecture, Classification Algorithms, Model Evaluation, Regression Analysis
状态：免费试用您将获得的技能: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Recurrent Neural Networks (RNNs), Model Deployment, Reinforcement Learning, Artificial Intelligence, Classification Algorithms, Classification And Regression Tree (CART), Tensorflow, Machine Learning Algorithms, Keras (Neural Network Library), Artificial Neural Networks, Deep Learning, Machine Learning, Decision Tree Learning, Predictive Analytics, Regression Analysis
状态：新状态：预览Simplilearn
您将获得的技能: Convolutional Neural Networks, Image Analysis, Computer Vision, Deep Learning, Artificial Neural Networks, Model Evaluation, Data Preprocessing, Python Programming
总之，以下是 10 最受欢迎的 convolutional neural network 课程
- Learning Deep Learning: Unit 2: Pearson
- Introduction Course to Autoencoders, VAEs, and GANs: Simplilearn
- 构建基本的生成对抗网络 (GAN): DeepLearning.AI
- Image Classification with Keras: Build & Optimize: EDUCBA
- Deep Learning with TensorFlow: Build Neural Networks: EDUCBA
- Image Generation with AI Training Course: Simplilearn
- Mastering Neural Networks and Model Regularization: Johns Hopkins University
- Introducción al deep learning contemporáneo: Universidad de los Andes
- 利用注意力模型进行自然语言处理: DeepLearning.AI
- Learning Deep Learning: Unit 1: Pearson
