无监督学习课程
无监督学习课程可以帮助您学习 Clustering 技术、Dimensionality Reduction 和 Anomaly Detection。您可以掌握数据预处理、Feature Extraction 和解释复杂数据集的技能。许多课程都会介绍 Scikit-learn 和 TensorFlow 等 Python 库等工具，这些工具支持在项目中实施这些方法。您还将探索客户细分、图像处理和推荐系统等领域的实际应用，提高从无标签数据中获得洞察力的能力。
热门无监督学习课程和认证
状态：免费试用DeepLearning.AI
您将获得的技能: 无监督学习, Algorithm, 人工智能, 降维, 机器学习, 强化学习, 人工神经网络, 深度学习, 数据伦理, 监督学习, 异常检测
状态：新状态：免费试用University of Colorado Boulder
您将获得的技能: Feature Engineering, Statistical Methods, Model Evaluation, Algorithms
状态：免费试用University of Michigan
您将获得的技能: Unsupervised Learning, Embeddings, Supervised Learning, Data Preprocessing, Python Programming, Exploratory Data Analysis
状态：免费试用多位教师
您将获得的技能: 预测建模, 数据预处理, 无监督学习, Scikit-learn （机器学习库）, NumPy, Transfer Learning, 人工智能, 机器学习, Jupyter, 强化学习, 数据伦理, Model Evaluation, 应用机器学习, 监督学习, 张力流, 深度学习, 随机森林算法, 决策树学习, 分类算法, 功能工程
状态：免费试用IBM
您将获得的技能: 机器学习算法, 无监督学习, 数据预处理, Scikit-learn （机器学习库）, Algorithm, 文本挖掘, 降维, 机器学习, 数据科学, 功能工程, 数据分析, 大数据
状态：免费试用您将获得的技能: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Random Forest Algorithm, Data Analysis, Predictive Modeling, Model Evaluation, Bayesian Network, Python Programming, Statistical Modeling, Classification Algorithms
是什么让您今天来到 Coursera？
状态：免费试用O.P. Jindal Global University
您将获得的技能: Anomaly Detection, Dimensionality Reduction, Unsupervised Learning, Customer Analysis, Marketing Analytics, Data Mining, Feature Engineering, Autoencoders, Applied Machine Learning, Machine Learning Algorithms, Machine Learning Methods, Marketing, Statistical Machine Learning, Target Audience, Python Programming, Market Analysis, Exploratory Data Analysis, Model Evaluation, Algorithms
状态：免费试用University of Colorado Boulder
您将获得的技能: Model Evaluation, Applied Machine Learning, Unsupervised Learning, Classification And Regression Tree (CART), Decision Tree Learning, Artificial Neural Networks, Classification Algorithms, Supervised Learning, Machine Learning Algorithms, Random Forest Algorithm, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Statistics
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Transfer Learning, Large Language Modeling, Natural Language Processing, Vision Transformer (ViT), Deep Learning, PyTorch (Machine Learning Library), Tensorflow, Artificial Neural Networks, Embeddings, Computer Vision
状态：免费试用您将获得的技能: Dimensionality Reduction, Unsupervised Learning, Deep Learning, Model Evaluation, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Feature Engineering, Artificial Neural Networks, Supervised Learning, Statistical Machine Learning, Anomaly Detection, Classification Algorithms, Performance Tuning
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：新状态：免费试用Dartmouth College
您将获得的技能: Supervised Learning, Predictive Modeling, Logistic Regression, Statistical Modeling, Model Evaluation, Machine Learning, Machine Learning Algorithms, Classification Algorithms, Regression Analysis, Probability & Statistics, Linear Algebra
总之，以下是 10 最受欢迎的 unsupervised learning 课程
- 无监督学习、推荐器、强化学习: DeepLearning.AI
- Introduction to Machine Learning: Unsupervised Learning: University of Colorado Boulder
- Applied Unsupervised Learning in Python: University of Michigan
- 机器学习: DeepLearning.AI
- 无监督机器学习: IBM
- The Nuts and Bolts of Machine Learning: Google
- Unsupervised Learning and Its Applications in Marketing: O.P. Jindal Global University
- Trees, SVM and Unsupervised Learning: University of Colorado Boulder
- Sequence Modeling, Transformers, and Transfer Learning: Packt
- Advanced ML Algorithms & Unsupervised Learning: Packt
