个结果，搜索词为 "transfer learning"
状态：免费试用DeepLearning.AI
您将获得的技能: 机器学习, PyTorch（机器学习库）, 拥抱的脸, 卷积神经网络, 自然语言处理, 数据预处理, 张力流, 人工神经网络, 计算机视觉, 监督学习, 调试, 嵌入, 迁移学习, 应用机器学习, 递归神经网络 (RNN), Keras（神经网络库）, 性能调整, 人工智能和机器学习（AI/ML）, 图像分析, 深度学习
您将获得的技能: Transfer Learning, Tensorflow, Natural Language Processing, Keras (Neural Network Library), Embeddings, Deep Learning, Classification Algorithms, Model Evaluation, Machine Learning, Software Visualization
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Artificial Neural Networks, Deep Learning, Matplotlib, Convolutional Neural Networks, Linear Algebra, Image Analysis, Data Visualization, NumPy, Machine Learning Algorithms, Keras (Neural Network Library), Pandas (Python Package), Seaborn, Artificial Intelligence and Machine Learning (AI/ML), Data Science, Applied Machine Learning, Tensorflow, Data Analysis, Artificial Intelligence, Machine Learning
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IBM
您将获得的技能: 机器学习, 模型评估, 卷积神经网络, 生成式人工智能, 计算机视觉, 无监督学习, 人工神经网络, 强化学习, 递归神经网络 (RNN), 降维, 迁移学习, 自动编码器, Keras（神经网络库）, Machine Learning 方法, 人工智能和机器学习（AI/ML）, 生成对抗网络 (GAN), 深度学习
Google Cloud
您将获得的技能: 机器学习, 卷积神经网络, 张力流, 迁移学习, Keras（神经网络库）, 图像分析, 深度学习, 应用机器学习
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: Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Keras (Neural Network Library), Image Analysis, Deep Learning, Tensorflow, Computer Vision, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Data Manipulation, Data Transformation, Financial Forecasting, Data Visualization, Time Series Analysis and Forecasting, Exploratory Data Analysis, Python Programming, Customer Analysis, Applied Machine Learning, Cloud Computing
状态：新状态：免费试用您将获得的技能: Tensorflow, Computer Vision, Model Evaluation, Convolutional Neural Networks, Deep Learning, Amazon Elastic Compute Cloud, Transfer Learning, Image Analysis, Amazon Web Services, Artificial Neural Networks, Keras (Neural Network Library), Model Deployment, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Feature Engineering, Data Preprocessing, Classification Algorithms, Application Development, Python Programming, Network Architecture
状态：新状态：免费试用您将获得的技能: Sampling (Statistics), Matplotlib, Data Analysis, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, Model Evaluation, R Programming, Probability, Python Programming, Scikit Learn (Machine Learning Library), Data Preprocessing, Linear Algebra, Applied Machine Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML)
状态：免费试用University of Alberta
您将获得的技能: 模型评估, 机器学习, 概率分布, 抽样（统计）, 线性代数, 模拟, Algorithm, 人工神经网络, 强化学习, 机器学习算法, 马尔可夫模型, 功能工程, 人工智能, 性能调整, 监督学习, 人工智能和机器学习（AI/ML）, 性能测试, 伪代码, 深度学习
状态：新状态：免费试用您将获得的技能: Vision Transformer (ViT), Prompt Engineering, PyTorch (Machine Learning Library), Model Deployment, Transfer Learning, Hugging Face, Natural Language Processing, MLOps (Machine Learning Operations), Large Language Modeling, Cloud Deployment, Computer Vision, Generative AI, Image Analysis, Application Deployment, Generative Model Architectures, Embeddings, Data Preprocessing, Model Evaluation
状态：免费试用多位教师
您将获得的技能: 模型评估, 机器学习, 预测建模, 张力流, Scikit-learn （机器学习库）, 数据预处理, 无监督学习, 迁移学习, 随机森林算法, 强化学习, 数据伦理, 分类算法, 应用机器学习, 决策树学习, Jupyter, 监督学习, 人工智能, NumPy, 深度学习, 功能工程
总之，以下是 10 最受欢迎的 transfer learning 课程
- 深度学习: DeepLearning.AI
- Transfer Learning for NLP with TensorFlow Hub: Coursera
- Deep Learning with Real-World Projects: Packt
- Advanced CNNs, Transfer Learning, and Recurrent Networks: Packt
- 深度学习和强化学习: IBM
- 利用迁移学习对猫狗图像进行分类: Google Cloud
- Deep Learning with Python: CNN, ANN & RNN: EDUCBA
- AI Deep Learning Projects with TensorFlow: EDUCBA
- AI Machine Learning with R & Python Projects: EDUCBA
- 强化学习: University of Alberta
