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  • Pattern Recognition

Pattern Recognition Courses

Pattern recognition courses can help you learn techniques for data classification, feature extraction, and image analysis. You can build skills in statistical modeling, machine learning algorithms, and neural network design. Many courses introduce tools like Python libraries such as TensorFlow and scikit-learn, which are used to implement these techniques in projects involving AI and artificial intelligence applications.


Popular Pattern Recognition Courses and Certifications


  • D

    Duke University

    Introduction to Machine Learning

    Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Transfer Learning, Reinforcement Learning, Convolutional Neural Networks, Deep Learning, Image Analysis, Applied Machine Learning, Natural Language Processing, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Neural Networks, Supervised Learning, Unsupervised Learning, Python Programming, Computer Vision, Medical Imaging

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.8K reviews

    Intermediate · Course · 1 - 3 Months

  • N

    Northeastern University

    Machine Learning for Engineers: Algorithms and Applications

    Skills you'll gain: Model Evaluation, Supervised Learning, Statistical Machine Learning, Machine Learning Algorithms, Unsupervised Learning, PyTorch (Machine Learning Library), Applied Machine Learning, Statistical Methods, Statistical Modeling, Machine Learning, Machine Learning Software, Statistical Analysis, Artificial Intelligence and Machine Learning (AI/ML), Regression Analysis, Classification Algorithms, Algorithms, Predictive Modeling, Dimensionality Reduction, Complex Problem Solving

    Intermediate · Course · 1 - 4 Weeks

  • E

    Edureka

    AI Applications: Computer Vision and Speech Recognition

    Skills you'll gain: Computer Vision, Applied Machine Learning, Digital Signal Processing

    Intermediate · Course · 1 - 4 Weeks

  • Status: Bestseller
    Bestseller
    U
    I
    I

    Multiple educators

    Data Science Foundations

    Skills you'll gain: Dashboard, Web Scraping, Pseudocode, Algorithms, Data Literacy, Data Mining, Data Analysis, Data Presentation, Correlation Analysis, Pandas (Python Package), NumPy, Data Import/Export, Probability & Statistics, Programming Principles, Predictive Modeling, Real Time Data, Data Science, Unsupervised Learning, Machine Learning, Project Management

    4.6
    Rating, 4.6 out of 5 stars
    ·
    117K reviews

    Beginner · Specialization · 3 - 6 Months

  • D

    DeepLearning.AI

    Advanced Computer Vision with TensorFlow

    Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Transfer Learning, Convolutional Neural Networks, Keras (Neural Network Library), Deep Learning, Classification Algorithms, Model Evaluation, Visualization (Computer Graphics), Network Architecture

    4.7
    Rating, 4.7 out of 5 stars
    ·
    533 reviews

    Intermediate · Course · 1 - 4 Weeks

  • U

    UNSW Sydney (The University of New South Wales)

    Remote Sensing Image Acquisition, Analysis and Applications

    Skills you'll gain: Image Analysis, Unsupervised Learning, Geospatial Information and Technology, Machine Learning Methods, Computer Vision, Feature Engineering, Spatial Analysis, Machine Learning, Dimensionality Reduction, Convolutional Neural Networks, Deep Learning, Supervised Learning, Classification Algorithms, Probability & Statistics, Artificial Neural Networks

    4.7
    Rating, 4.7 out of 5 stars
    ·
    181 reviews

    Intermediate · Course · 3 - 6 Months

  • U

    University of Colorado Boulder

    Introduction to Computer Vision

    Skills you'll gain: Image Analysis, Computer Vision, Deep Learning, Convolutional Neural Networks, Computer Graphics, Machine Learning Methods, Artificial Intelligence, Data Ethics, Microsoft Excel, Generative AI, Linear Algebra, Feature Engineering, Digital Signal Processing

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    32 reviews

    Beginner · Course · 1 - 4 Weeks

  • N

    Northeastern University

    Statistical Learning for Engineering Part 1

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Machine Learning Software, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Logistic Regression, Unstructured Data, Model Evaluation, Dimensionality Reduction

    Intermediate · Course · 1 - 3 Months

  • I

    IBM

    AI Workflow: Machine Learning, Visual Recognition and NLP

    Skills you'll gain: Model Evaluation, Tensorflow, Supervised Learning, Artificial Neural Networks, Regression Analysis, Machine Learning Methods, Applied Machine Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Image Analysis, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Decision Tree Learning, Natural Language Processing, Scikit Learn (Machine Learning Library), Convolutional Neural Networks, Computer Vision, Data Science, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    90 reviews

    Advanced · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Introduction to Neural Networks

    Skills you'll gain: Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Image Analysis, Machine Learning, Computer Vision, Model Evaluation, Supervised Learning, Algorithms, Statistical Methods, Linear Algebra, Probability

    4.1
    Rating, 4.1 out of 5 stars
    ·
    9 reviews

    Intermediate · Course · 1 - 3 Months

  • C

    Columbia University

    Features and Boundaries

    Skills you'll gain: Image Analysis, Computer Vision, Computer Graphics, Algorithms, Linear Algebra, Machine Learning Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    54 reviews

    Beginner · Course · 1 - 3 Months

  • M

    MathWorks

    Introduction to Computer Vision

    Skills you'll gain: Image Analysis, Computer Vision, Matlab, Geospatial Information and Technology, Medical Imaging, Estimation, Artificial Intelligence and Machine Learning (AI/ML), Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    58 reviews

    Intermediate · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular pattern recognition courses

  • Introduction to Machine Learning: Duke University
  • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
  • AI Applications: Computer Vision and Speech Recognition: Edureka
  • Data Science Foundations: University of London
  • Advanced Computer Vision with TensorFlow: DeepLearning.AI
  • Remote Sensing Image Acquisition, Analysis and Applications: UNSW Sydney (The University of New South Wales)
  • Introduction to Computer Vision: University of Colorado Boulder
  • Statistical Learning for Engineering Part 1: Northeastern University
  • AI Workflow: Machine Learning, Visual Recognition and NLP: IBM
  • Introduction to Neural Networks: Johns Hopkins University

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