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: 机器学习, 数据伦理, Algorithm, 监督学习, 人工智能, 降维, 强化学习, 人工神经网络, 无监督学习, 深度学习, 异常检测
状态：新状态：免费试用University of Colorado Boulder
您将获得的技能: Statistical Machine Learning, Model Evaluation, Data Transformation, Algorithms
状态：免费试用多位教师
您将获得的技能: 机器学习, 数据伦理, 分类算法, Scikit-learn （机器学习库）, 监督学习, 人工智能, NumPy, 强化学习, 模型评估, 迁移学习, 无监督学习, Jupyter, 数据预处理, 决策树学习, 应用机器学习, 深度学习, 随机森林算法, 张力流, 功能工程, 预测建模
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：免费试用您将获得的技能: Feature Engineering, Model Evaluation, Advanced Analytics, Statistical Machine Learning, Unsupervised Learning, Machine Learning, Data Ethics, Supervised Learning, Decision Tree Learning, Random Forest Algorithm, Classification Algorithms, Python Programming, Performance Tuning
状态：免费试用IBM
您将获得的技能: 机器学习, 机器学习算法, Scikit-learn （机器学习库）, Algorithm, 降维, 模型评估, 统计机器学习, 无监督学习, 数据挖掘, 性能指标, 应用机器学习, 数据预处理
是什么让您今天来到 Coursera？
状态：免费试用您将获得的技能: 机器学习, 分类算法, Scikit-learn （机器学习库）, 监督学习, 降维, 模型评估, 回归分析, 无监督学习, 决策树学习, Python 程序设计, 逻辑回归, 应用机器学习, 预测建模, 数据预处理
状态：免费试用O.P. Jindal Global University
状态：新状态：免费试用Dartmouth College
您将获得的技能: Supervised Learning, Model Evaluation, Predictive Modeling, Regression Analysis, Machine Learning, Statistical Modeling, Logistic Regression, Probability & Statistics, Classification Algorithms
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DeepLearning.AI
您将获得的技能: 数据操作, 机器学习, 数据转换, 调试, 降维, 代数, NumPy, 线性代数, 应用数学, Python 程序设计, Jupyter, 高等数学
状态：新状态：免费试用您将获得的技能: Dimensionality Reduction, R Programming, Time Series Analysis and Forecasting, Applied Machine Learning, Unsupervised Learning, Predictive Modeling, Machine Learning, Text Mining, Classification Algorithms, Artificial Neural Networks, Data Mining, Feature Engineering, Data Preprocessing, Model Evaluation, Exploratory Data Analysis
与 unsupervised learning 相关的搜索
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
- 机器学习: DeepLearning.AI
- Applied Unsupervised Learning in Python: University of Michigan
- The Nuts and Bolts of Machine Learning: Google
- 无监督机器学习: IBM
- 使用 Python 进行机器学习: IBM
- Unsupervised Learning and Its Applications in Marketing: O.P. Jindal Global University
- Machine Learning Fundamentals: Dartmouth College
- Advanced ML Algorithms & Unsupervised Learning: Packt
