Unsupervised Learning

Unsupervised Learning is a type of machine learning that uses algorithms to analyze and cluster unlabeled data. Coursera's Unsupervised Learning catalogue teaches you how to implement this self-guided learning method to discover hidden patterns and correlations in raw, unclassified data. You'll learn about various unsupervised learning models including clustering, anomaly detection, neural networks, and dimensionality reduction. Gain knowledge about the different methods of data analysis, understand how to use clustering and association techniques, and master the art of interpreting and visualizing complex datasets. This skill will enable you to make predictions, enhance data privacy, and implement machine learning models more effectively.

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Results for "Unsupervised Learning"

  • Skills you'll gain: Unsupervised Learning, Dimensionality Reduction, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Applied Machine Learning, Data Preprocessing, Text Mining, Machine Learning, Big Data, Model Evaluation, Performance Metric

  • Skills you'll gain: Unsupervised Learning, Embeddings, Applied Machine Learning, Data Quality, Unstructured Data, Machine Learning Methods, Anomaly Detection, Data Preprocessing, Data Transformation, Python Programming, Exploratory Data Analysis, Model Evaluation

  • Skills you'll gain: Anomaly Detection, Feature Engineering, Fraud detection, Unsupervised Learning, Continuous Monitoring, Autoencoders, MLOps (Machine Learning Operations), Machine Learning Methods, Statistical Machine Learning, Model Training, Time Series Analysis and Forecasting, System Monitoring, Applied Machine Learning, Model Deployment, Statistical Analysis, Taxonomy

  • Skills you'll gain: Unsupervised Learning, Applied Machine Learning, Responsible AI, Data Ethics, Machine Learning, Supervised Learning, Artificial Intelligence, Reinforcement Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction

  • University of Colorado Boulder

    Skills you'll gain: Model Evaluation, Applied Machine Learning, Unsupervised Learning, Decision Tree Learning, Artificial Neural Networks, Machine Learning Methods, Classification Algorithms, Supervised Learning, Statistical Machine Learning, Machine Learning Algorithms, Random Forest Algorithm, Predictive Modeling, Applied Mathematics, Dimensionality Reduction, Statistics

  • Skills you'll gain: Anomaly Detection, Dimensionality Reduction, Unsupervised Learning, Customer Analysis, Marketing Analytics, Data Mining, Customer Insights, Autoencoders, Data-Driven Marketing, Applied Machine Learning, Machine Learning Algorithms, Machine Learning Methods, Marketing, Statistical Machine Learning, Target Audience, Supervised Learning, Python Programming, Algorithms

  • Skills you'll gain: PyTorch (Machine Learning Library), Model Optimization, Keras (Neural Network Library), Deep Learning, Convolutional Neural Networks, Reinforcement Learning, Transfer Learning, Autoencoders, Generative AI, Unsupervised Learning, Tensorflow, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Generative Model Architectures, Model Training, Logistic Regression, Image Analysis, Applied Machine Learning, Regression Analysis

  • Skills you'll gain: Generative AI, Model Evaluation, Supervised Learning, Generative Model Architectures, Recurrent Neural Networks (RNNs), Unsupervised Learning, Data Preprocessing, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Data Collection, Model Optimization, Convolutional Neural Networks, Model Deployment, Transfer Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Machine Learning Software

  • Skills you'll gain: Model Optimization, Dimensionality Reduction, Unsupervised Learning, Deep Learning, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Anomaly Detection, Classification Algorithms, Linear Algebra

  • Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, Retrieval-Augmented Generation, PyTorch (Machine Learning Library), Computer Vision, Unsupervised Learning, Generative Model Architectures, Prompt Patterns, Generative AI, PySpark, Model Optimization, Keras (Neural Network Library), Supervised Learning, LLM Application, Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science

  • Johns Hopkins University

    Skills you'll gain: Computer Vision, Model Evaluation, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Data Preprocessing, Dimensionality Reduction, Machine Learning Methods, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Model Training, Machine Learning, Deep Learning, Model Optimization

  • Imperial College London

    Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Unsupervised Learning, Applied Mathematics, Statistical Methods, Descriptive Statistics, Model Optimization, Mathematical Software, Machine Learning Methods, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Geometry, Artificial Neural Networks, Data Science, Data Manipulation