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), Tensorflow, Natural Language Processing, Deep Learning, Predictive Modeling, Time Series Analysis and Forecasting, Artificial Neural Networks, Machine Learning, Embeddings, Data Preprocessing
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Classification Algorithms, Transfer Learning, Applied Machine Learning, Image Analysis, Model Evaluation, Artificial Neural Networks, Computer Vision, Data Preprocessing
状态：免费试用您将获得的技能: Model Evaluation, Deep Learning, Data Preprocessing, Data Manipulation, Applied Machine Learning, Model Deployment, Artificial Neural Networks, Embeddings, Matplotlib
您将获得的技能: Large Language Modeling, Deep Learning, Data Preprocessing, Keras (Neural Network Library), Tensorflow, Python Programming, Artificial Intelligence and Machine Learning (AI/ML), Generative Model Architectures, Natural Language Processing
状态：免费试用IBM
您将获得的技能: 时间序列分析和预测, 自动编码器, Python 程序设计, 统计方法, 强化学习, 生成对抗网络 (GAN), 深度学习, 数据分析, 递归神经网络 (RNN), 机器学习, 回归分析, 功能工程, 卷积神经网络, 探索性数据分析, 监督学习, 无监督学习, 分类算法, 数据预处理, 数据科学, 降维
状态：免费试用University of Washington
您将获得的技能: 人工智能, 模型评估, 决策树学习, 预测建模, 深度学习, 统计建模, 逻辑回归, 统计机器学习, 贝叶斯统计, 回归分析, 功能工程, 机器学习, 计算机视觉, 无监督学习, 应用机器学习, 分类算法, 监督学习, 数据挖掘, 图像分析, 数据预处理
状态：免费试用多位教师
您将获得的技能: 人工智能, 决策树学习, 张力流, 预测建模, 模型评估, 随机森林算法, 强化学习, 深度学习, 应用机器学习, 机器学习, 无监督学习, Jupyter, 监督学习, Scikit-learn （机器学习库）, NumPy, 分类算法, 功能工程, 数据预处理, 数据伦理, 迁移学习
状态：免费试用University of Illinois Urbana-Champaign
您将获得的技能: 图论, 自动编码器, 深度学习, 卷积神经网络, Machine Learning 方法, 嵌入, 模型评估, 生成对抗网络 (GAN), 医疗保健, 应用机器学习, 医疗保健项目管理, 人工神经网络, 健康信息管理, 模型部署, 机器学习, 大数据, 健康信息学, 递归神经网络 (RNN), 监督学习, 图像分析
状态：预览O.P. Jindal Global University
您将获得的技能: Model Evaluation, Supervised Learning, Scikit Learn (Machine Learning Library), Tensorflow, Applied Machine Learning, Artificial Neural Networks, Python Programming, NumPy, Matplotlib, Deep Learning, Image Analysis, Machine Learning, Embeddings, Pandas (Python Package), Convolutional Neural Networks, Natural Language Processing, Regression Analysis
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
状态：新您将获得的技能: Autoencoders, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Tensorflow, Classification Algorithms, Model Evaluation
与 deep reinforcement learning 相关的搜索
总之，以下是 10 最受欢迎的 deep reinforcement learning 课程
- Recommender Systems Complete Course Beginner to Advanced: Packt
- Building and Training Neural Networks with PyTorch: Packt
- Recommender Systems: An Applied Approach using Deep Learning: Packt
- Advanced Chatbots with Deep Learning and Python: Packt
- 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
- Machine Learning: O.P. Jindal Global University
- Deep Learning with PyTorch : Image Segmentation : Coursera
