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：免费试用DeepLearning.AI
您将获得的技能: 生成式对抗网络（GANs）, 自动编码器, 深度学习, 张力流, Transfer Learning, 人工神经网络, 卷积神经网络, 迁移学习, 生成式人工智能, 生成模型架构, 图像分析
状态：免费试用DeepLearning.AI
您将获得的技能: 数据伦理, PyTorch（机器学习库）, 生成式对抗网络（GANs）, 负责任的人工智能, 信息隐私, 数据综合, 无监督学习, 卷积神经网络, 生成式人工智能, 图像分析
状态：免费您将获得的技能: Tensorflow, Convolutional Neural Networks, Image Analysis, Python Programming, Jupyter, Artificial Neural Networks, Deep Learning, Software Visualization, Machine Learning
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)
您将获得的技能: Tensorflow, Convolutional Neural Networks, Keras (Neural Network Library), Matplotlib, Artificial Neural Networks, Image Analysis, Deep Learning, Applied Machine Learning, Python Programming, Model Evaluation, Adaptability, Problem Solving
状态：免费试用您将获得的技能: Autoencoders, Shiny (R Package), Deep Learning, Recurrent Neural Networks (RNNs), Transfer Learning, Convolutional Neural Networks, Image Analysis, PyTorch (Machine Learning Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Tensorflow, Predictive Modeling, Dimensionality Reduction, Classification Algorithms, Time Series Analysis and Forecasting, Model Evaluation
状态：新状态：免费试用您将获得的技能: Convolutional Neural Networks, Model Evaluation, Keras (Neural Network Library), Image Analysis, Deep Learning, Applied Machine Learning, Computer Vision, Dimensionality Reduction, PyTorch (Machine Learning Library), Tensorflow, Machine Learning Methods, Data Preprocessing, Performance Tuning, Artificial Intelligence
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：免费试用您将获得的技能: Model Evaluation, Convolutional Neural Networks, Keras (Neural Network Library), Image Analysis, Data Preprocessing, Deep Learning, Computer Vision, Tensorflow, Python Programming, Cloud Computing, Development Environment
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
您将获得的技能: PyTorch (Machine Learning Library), Computer Vision, NumPy, Matplotlib, Convolutional Neural Networks, Deep Learning, Pandas (Python Package), Image Analysis, Python Programming, Artificial Neural Networks, Data Manipulation
状态：免费试用您将获得的技能: Exploratory Data Analysis, Model Deployment, Keras (Neural Network Library), Transfer Learning, Data Analysis, Data Preprocessing, Image Analysis, Deep Learning, Classification Algorithms, Applied Machine Learning, Computer Vision, Model Evaluation, Machine Learning, Performance Tuning
总之，以下是 10 最受欢迎的 convolutional neural network 课程
- 使用 TensorFlow 进行生成式深度学习: DeepLearning.AI
- 应用生成式对抗网络 (GAN): DeepLearning.AI
- Visualizing Filters of a CNN using TensorFlow: Coursera
- Image Classification with Keras: Build & Optimize: EDUCBA
- CNNs with TensorFlow: Basics of Machine Learning: Coursera
- Advanced Machine Learning and Deep Learning: Packt
- Foundations of Model Optimization and Deep Learning: Packt
- Mastering Neural Networks and Model Regularization: Johns Hopkins University
- Master CNNs with Python: Build, Train & Evaluate Models: EDUCBA
- Learning Deep Learning: Unit 2: Pearson
