深度强化学习课程
Deep Reinforcement Learning 课程可以帮助您学习强化学习、神经网络和策略梯度的原理。您可以掌握算法设计、奖励优化和环境模拟方面的技能。许多课程介绍了 TensorFlow 和 PyTorch 等工具，这些工具支持实现 AI 模型，以及在复杂环境中训练代理的技术。
热门 Deep Learning 课程和认证
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Deep Learning, Artificial Neural Networks, Image Analysis, Keras (Neural Network Library), Applied Machine Learning, Tensorflow, PyTorch (Machine Learning Library), Natural Language Processing, Network Architecture, Model Evaluation, Performance Tuning
状态：免费试用您将获得的技能: Artificial Neural Networks, Deep Learning, Convolutional Neural Networks, Image Analysis, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Machine Learning Methods, Network Architecture, Artificial Intelligence, Network Model, Machine Learning, Classification Algorithms, Data Processing
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Artificial Intelligence, Applied Machine Learning, Python Programming, Model Evaluation
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Model Deployment, Keras (Neural Network Library), Deep Learning, Tensorflow, Artificial Neural Networks, Convolutional Neural Networks, Application Frameworks, Artificial Intelligence, Machine Learning Methods, Image Analysis, Data Preprocessing
状态：免费试用IBM
您将获得的技能: Python 程序设计, 生成对抗网络 (GAN), 卷积神经网络, 数据预处理, 降维, 分类算法, 统计方法, 递归神经网络 (RNN), 功能工程, 无监督学习, 自动编码器, 探索性数据分析, 监督学习, 深度学习, 强化学习, 数据科学, 数据分析, 机器学习, 回归分析, 时间序列分析和预测
状态：免费试用University of Washington
您将获得的技能: 人工智能, 计算机视觉, 数据预处理, 统计建模, 统计机器学习, 贝叶斯统计, 分类算法, 深度学习, 逻辑回归, 预测建模, 决策树学习, 功能工程, 无监督学习, 应用机器学习, 图像分析, 机器学习, 数据挖掘, 回归分析, 监督学习, Model Evaluation
状态：免费试用多位教师
您将获得的技能: 人工智能, Scikit-learn （机器学习库）, Transfer Learning, 数据预处理, NumPy, 分类算法, 预测建模, 无监督学习, 随机森林算法, 强化学习, 数据伦理, 决策树学习, Jupyter, 应用机器学习, 张力流, Model Evaluation, 监督学习, 深度学习, 功能工程, 机器学习
状态：免费试用University of Illinois Urbana-Champaign
您将获得的技能: 生成对抗网络 (GAN), 卷积神经网络, 大数据, 图论, 人工神经网络, 医学科学与研究, 医疗保健, 模型部署, 深度学习, 自动编码器, 应用机器学习, Machine Learning 方法, 嵌入, 递归神经网络 (RNN), 医疗保健项目管理, 监督学习, 机器学习, 图像分析, 健康信息学, Model Evaluation
状态：免费试用DeepLearning.AI
您将获得的技能: 人工智能, Algorithm, 降维, 无监督学习, 深度学习, 监督学习, 数据伦理, 人工神经网络, 强化学习, 机器学习, 异常检测
您将获得的技能: PyTorch (Machine Learning Library), Model Evaluation, Convolutional Neural Networks, Transfer Learning, Image Analysis, Deep Learning, Python Programming
状态：免费试用University of Pennsylvania
您将获得的技能: Data Preprocessing, PyTorch (Machine Learning Library), Deep Learning, Artificial Neural Networks, Machine Learning Algorithms, Supervised Learning, Machine Learning, Artificial Intelligence
您将获得的技能: Autoencoders, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Tensorflow, Classification Algorithms, Model Evaluation
总之，以下是 10 最受欢迎的 deep reinforcement learning 课程
- Advanced CNNs, Transfer Learning, and Recurrent Networks: Packt
- Foundations of Deep Learning and Neural Networks: Packt
- Practical Deep Learning with Python: Edureka
- Deep Learning Frameworks and Neural Networks Simplified: Simplilearn
- IBM 机器学习: IBM
- 机器学习: University of Washington
- 机器学习: DeepLearning.AI
- 医疗保健领域的深度学习: University of Illinois Urbana-Champaign
- 无监督学习、推荐器、强化学习: DeepLearning.AI
- Deep Learning with PyTorch : Image Segmentation : Coursera
