Keras 课程
Keras 课程可以帮助您学习神经网络设计、模型训练和性能评估技术。您可以掌握优化 Hyperparameter、实施卷积层和递归层以及在各种应用中使用 Transfer Learning 的技能。许多课程介绍了 TensorFlow 和 Python 等工具，这些工具支持开发 AI 模型并将其部署到实际工作中。
热门 Keras 课程和认证
状态：免费试用您将获得的技能: 回归分析, 网络架构, 递归神经网络 (RNN), Keras（神经网络库）, 卷积神经网络, 人工神经网络, 深度学习, Transfer Learning, 机器学习, 自然语言处理, Model Evaluation, 应用机器学习, 分类与回归树 (CART), 图像分析, 自动编码器
状态：免费试用状态：人工智能技能您将获得的技能: PyTorch (Machine Learning Library), Transfer Learning, Model Evaluation, Vision Transformer (ViT), Keras (Neural Network Library), Deep Learning, Convolutional Neural Networks, Reinforcement Learning, Autoencoders, Unsupervised Learning, Tensorflow, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Statistical Methods, Logistic Regression, Image Analysis, Data Preprocessing, Applied Machine Learning, Model Deployment
状态：免费试用您将获得的技能: 生成对抗网络 (GAN), 计算机视觉, 卷积神经网络, 强化学习, 递归神经网络 (RNN), Keras（神经网络库）, 深度学习, Transfer Learning, 无监督学习, Model Evaluation, 张力流, 性能调整, 自动编码器
状态：免费试用IBM
您将获得的技能: PyTorch（机器学习库）, Prompt Engineering, 计算机视觉, PySpark, 生成式人工智能, Python 程序设计, 数据科学, Keras（神经网络库）, 矢量数据库, 视觉转换器（ViT）, 检索-增强生成, Model Evaluation, 监督学习, 机器学习, 生成模型架构, Apache Spark, 无监督学习, Transfer Learning, 大型语言模型, LLM 申请
状态：免费试用您将获得的技能: Generative Adversarial Networks (GANs), Exploratory Data Analysis, Model Deployment, Keras (Neural Network Library), NumPy, Applied Machine Learning, Transfer Learning, PyTorch (Machine Learning Library), Predictive Modeling, Matplotlib, Data Analysis, Data Preprocessing, Development Environment, Pandas (Python Package), Deep Learning, Artificial Neural Networks, Image Analysis, Artificial Intelligence, Machine Learning, Data Science
状态：新状态：免费试用您将获得的技能: Embeddings, Natural Language Processing, Keras (Neural Network Library), Generative AI, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks (RNNs), Model Evaluation, Image Analysis, Artificial Neural Networks, Text Mining, Computer Vision, Data Preprocessing, Tensorflow, Deep Learning, Model Deployment, Applied Machine Learning, Google Cloud Platform, Jupyter, Matplotlib
是什么让您今天来到 Coursera？
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Transfer Learning, Tensorflow, Artificial Neural Networks, Embeddings, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Image Analysis, Classification Algorithms, Convolutional Neural Networks, Natural Language Processing, Computer Vision, Forecasting, Supervised Learning, Machine Learning Algorithms, Machine Learning, Predictive Analytics, Model Evaluation, Predictive Modeling
状态：免费试用Imperial College London
您将获得的技能: 数据管道, 计算机视觉, 卷积神经网络, 人工神经网络, Transfer Learning, 监督学习, Model Evaluation, 深度学习, 贝叶斯统计, 递归神经网络 (RNN), Keras（神经网络库）, 模型部署, 应用机器学习, 数据预处理, 生成模型架构, 自然语言处理, 张力流, 自动编码器, 图像分析, 概率分布
状态：新状态：预览您将获得的技能: Artificial Intelligence and Machine Learning (AI/ML)
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: Transfer Learning, Keras (Neural Network Library), Embeddings, Deep Learning, Image Analysis, Computer Vision, Natural Language Processing, Data Preprocessing
状态：免费试用您将获得的技能: Prompt Engineering, Prompt Patterns, LangChain, Large Language Modeling, Retrieval-Augmented Generation, Exploratory Data Analysis, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, LLM Application, Keras (Neural Network Library), Supervised Learning, Model Evaluation, Data Analysis, Responsible AI, Vector Databases, Data Import/Export
是什么让您今天来到 Coursera？
总之，以下是 10 最受欢迎的 keras 课程
- 使用 Keras 的深度学习和神经网络简介: IBM
- IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
- 使用 Keras 和 TensorFlow 进行深度学习: IBM
- IBM 人工智能工程: IBM
- Keras Deep Learning & Generative Adversarial Networks (GAN): Packt
- Keras Deep Learning Projects with TensorFlow: EDUCBA
- Deep Learning with TensorFlow: Packt
- 用于深度学习的 TensorFlow 2: Imperial College London
- Analyze and Build Deep Learning Models with TensorFlow: EDUCBA
- CNNs with TensorFlow: Basics of Machine Learning: Coursera
