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。

您将获得的技能: 卷积神经网络, 迁移学习, 生成对抗网络 (GAN), 模型评估, 人工智能和机器学习(AI/ML), Keras(神经网络库), 强化学习, 无监督学习, 张力流, 性能调整, 递归神经网络 (RNN), 深度学习, 自动编码器, 人工神经网络
中级 · 课程 · 1-3 个月

New York University
您将获得的技能: Python 程序设计, 相关性分析, 金融交易, 决策树学习, Scikit-learn (机器学习库), 监督学习, 金融服务, 降维, 强化学习, 机器学习, 回归分析, 投资组合管理, 应用机器学习, 探索性数据分析, 无监督学习, 人工神经网络
中级 · 课程 · 1-4 周

您将获得的技能: Data Preprocessing, Applied Machine Learning, Unsupervised Learning, Correlation Analysis, Data Cleansing, R Programming, Data Quality, Machine Learning, Machine Learning Algorithms, Data Manipulation, Data Mining, Exploratory Data Analysis, Data Integrity
混合 · 课程 · 1-4 周

Board Infinity
您将获得的技能: Classification Algorithms, Data Preprocessing, Model Deployment, Model Evaluation, Decision Tree Learning, Regression Analysis, Logistic Regression
初级 · 课程 · 1-4 周

LearnKartS
您将获得的技能: AWS SageMaker, Data Preprocessing, Computer Vision, Natural Language Processing, Machine Learning, Data Wrangling, Reinforcement Learning, Artificial Intelligence, Model Deployment
初级 · 课程 · 1-4 周

University of Colorado Boulder
您将获得的技能: Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Statistical Machine Learning, Machine Learning, Regression Analysis, Supervised Learning, Data Science, Decision Tree Learning, Statistical Analysis, Classification Algorithms, Predictive Modeling, Artificial Neural Networks, Data Processing, Logistic Regression
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中级 · 课程 · 1-3 个月

您将获得的技能: Data Preprocessing, Model Deployment, Model Evaluation, Feature Engineering, Microsoft Azure, Applied Machine Learning, Machine Learning, Large Language Modeling, Data Cleansing, Supervised Learning, Data Transformation, Cloud Deployment, Data Ethics, CI/CD, Machine Learning Algorithms, Transfer Learning, Data Quality, Performance Tuning
中级 · 专项课程 · 1-3 个月

您将获得的技能: Autoencoders, Recurrent Neural Networks (RNNs), Classification Algorithms, Model Evaluation, Data Preprocessing
中级 · 课程 · 1-4 周

您将获得的技能: Predictive Modeling, Matplotlib, Applied Machine Learning, Seaborn, Data Visualization, Regression Analysis, Pandas (Python Package), Statistical Machine Learning, Statistical Analysis, Machine Learning, Supervised Learning, Data Science, Scikit Learn (Machine Learning Library), Probability & Statistics, Python Programming, Unsupervised Learning, Data Analysis, Decision Tree Learning, NumPy, Data Manipulation
中级 · 课程 · 1-3 个月

您将获得的技能: Apache Spark, PySpark, Retrieval-Augmented Generation, OpenAI API, Generative AI, Model Evaluation, Data Preprocessing, Large Language Modeling, Generative Adversarial Networks (GANs), Predictive Modeling, Matplotlib, Keras (Neural Network Library), Transfer Learning, Deep Learning, ChatGPT, Applied Machine Learning, Seaborn, Data Visualization, Regression Analysis, Machine Learning
中级 · 专项课程 · 3-6 个月

您将获得的技能: Rmarkdown, Autoencoders, Shiny (R Package), Deep Learning, Recurrent Neural Networks (RNNs), Transfer Learning, Model Evaluation, R (Software), Data Import/Export, Classification Algorithms, Reinforcement Learning, R Programming, Ggplot2, Data Manipulation, Convolutional Neural Networks, Plotly, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Dimensionality Reduction
初级 · 专项课程 · 3-6 个月

IBM
您将获得的技能: 生成式人工智能, Python 程序设计, 检索-增强生成, 迁移学习, 数据科学, Keras(神经网络库), Prompt Engineering, 监督学习, 计算机视觉, PyTorch(机器学习库), 模型评估, PySpark, LLM 申请, Apache Spark, 机器学习, 视觉转换器(ViT), 大型语言模型, 矢量数据库, 无监督学习, 生成模型架构
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中级 · 专业证书 · 3-6 个月