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"

  • DeepLearning.AI

    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

    4.9
    Rating, 4.9 out of 5 stars
    5.7K reviews

    Beginner · Course · 1 - 4 Weeks

  • IBM

    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

    4.7
    Rating, 4.7 out of 5 stars
    370 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New

    Packt

    Skills you'll gain: Anomaly Detection, PyTorch (Machine Learning Library), Forecasting, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Predictive Modeling, Deep Learning, Autoencoders, Predictive Analytics, Unsupervised Learning, Applied Machine Learning, Model Training, Generative Model Architectures, Convolutional Neural Networks, Exploratory Data Analysis, Model Optimization, Artificial Neural Networks, Data Preprocessing, Model Evaluation, Data Architecture

    Intermediate · Course · 1 - 3 Months

  • University of Michigan

    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

    4.9
    Rating, 4.9 out of 5 stars
    7 reviews

    Advanced · Course · 1 - 4 Weeks

  • Multiple educators

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning

    4.9
    Rating, 4.9 out of 5 stars
    39K reviews

    Beginner · Specialization · 1 - 3 Months

  • IBM

    Skills you'll gain: Model Evaluation, Predictive Modeling, Model Training, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

    4.5
    Rating, 4.5 out of 5 stars
    316 reviews

    Beginner · Course · 1 - 4 Weeks

  • 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

    Build toward a degree

    4.4
    Rating, 4.4 out of 5 stars
    9 reviews

    Intermediate · Course · 1 - 4 Weeks

  • IBM

    Skills you'll gain: Autoencoders, Generative AI, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Deep Learning, Unsupervised Learning, Machine Learning Methods, Transfer Learning, Model Optimization, Artificial Neural Networks, Keras (Neural Network Library), Machine Learning, Artificial Intelligence, Computer Vision, Applied Machine Learning, Model Training

    4.6
    Rating, 4.6 out of 5 stars
    304 reviews

    Intermediate · Course · 1 - 3 Months

  • Johns Hopkins University

    Skills you'll gain: Autoencoders, Recurrent Neural Networks (RNNs), Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Generative Model Architectures, Unsupervised Learning, Responsible AI, Data Ethics, Markov Model

    4
    Rating, 4 out of 5 stars
    7 reviews

    Intermediate · Course · 1 - 3 Months

  • Packt

    Skills you'll gain: Unsupervised Learning, Data Visualization, Machine Learning Methods, Machine Learning Algorithms, Applied Machine Learning, Scientific Visualization, Machine Learning, Model Training, Statistical Machine Learning, Data Mining, Statistical Methods, Algorithms, Python Programming, Development Environment

    Intermediate · Course · 1 - 3 Months

  • Johns Hopkins University

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Machine Learning Methods, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Model Optimization, Logistic Regression, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

  • Status: New

    John Wiley & Sons

    Skills you'll gain: Model Evaluation, Keras (Neural Network Library), Data Ethics, Image Analysis, AI Personalization, Model Training, Convolutional Neural Networks, Model Optimization, Machine Learning, Applied Machine Learning, Feature Engineering, Machine Learning Methods, Computer Vision, Supervised Learning, Data Preprocessing, Program Evaluation, Unsupervised Learning, Python Programming, Data Science, Algorithms

    Intermediate · Course · 1 - 3 Months