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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


  • 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

    Coursera

    Foundations of Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting, Decision Tree Learning, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling

    4.7
    Rating, 4.7 out of 5 stars
    ·
    12 reviews

    Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    Generative AI for Customer Support

    Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, Standard Operating Procedure, Customer Support, Product Support, Responsible AI, Real Time Data, Artificial Intelligence and Machine Learning (AI/ML), Customer experience improvement, Artificial Intelligence, AI Workflows, Data Ethics, Customer Insights, AI Personalization, Automation, Machine Learning, Natural Language Processing, Context Management

    4.7
    Rating, 4.7 out of 5 stars
    ·
    11K reviews

    Intermediate · Specialization · 1 - 3 Months

  • W

    Wesleyan University

    Machine Learning for Data Analysis

    Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Model Evaluation, Random Forest Algorithm, Applied Machine Learning, Predictive Analytics, Unsupervised Learning, Machine Learning Algorithms, Machine Learning, Data Analysis, Data Mining, Feature Engineering, Exploratory Data Analysis, Regression Analysis, Statistical Analysis, Python Programming

    4.2
    Rating, 4.2 out of 5 stars
    ·
    328 reviews

    Mixed · Course · 1 - 4 Weeks

  • C

    Columbia University

    Visual Perception

    Skills you'll gain: Computer Vision, Image Analysis, Dimensionality Reduction, Artificial Neural Networks, Machine Learning Methods, Unsupervised Learning, Deep Learning, Graph Theory, Machine Learning Algorithms, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    34 reviews

    Beginner · Course · 1 - 3 Months

  • D

    DeepLearning.AI

    Convolutional Neural Networks

    Skills you'll gain: Convolutional Neural Networks, Computer Vision, Image Analysis, Transfer Learning, Deep Learning, Artificial Neural Networks, Keras (Neural Network Library), Tensorflow, PyTorch (Machine Learning Library), Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
    ·
    43K reviews

    Intermediate · Course · 1 - 4 Weeks

  • 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

    Advanced Deep Learning Techniques for Computer Vision

    Skills you'll gain: Model Deployment, Anomaly Detection, Image Analysis, Computer Vision, Matlab, Deep Learning, Applied Machine Learning, PyTorch (Machine Learning Library), Transfer Learning, Data Synthesis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    15 reviews

    Beginner · Course · 1 - 4 Weeks

  • M

    MathWorks

    Introduction to Image Processing

    Skills you'll gain: Image Analysis, Matlab, Computer Vision, Spatial Data Analysis, Digital Signal Processing, Geospatial Information and Technology, Quantitative Research, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    207 reviews

    Beginner · Course · 1 - 4 Weeks

  • M

    MathWorks

    Machine Learning for Computer Vision

    Skills you'll gain: Computer Vision, Model Evaluation, Image Analysis, Matlab, Data Preprocessing, Machine Learning, Classification Algorithms, Machine Learning Algorithms, Deep Learning, Data Validation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    23 reviews

    Beginner · 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

  • E

    EDUCBA

    Face Recognition with Keras: Detect & Classify

    Skills you'll gain: Convolutional Neural Networks, Keras (Neural Network Library), Image Analysis, Computer Vision, Tensorflow, Data Preprocessing, Deep Learning, Embeddings, Model Deployment, Applied Machine Learning, Python Programming, Supervised Learning, NumPy, Model Evaluation

    Mixed · Course · 1 - 4 Weeks

1234…161

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

  • Introduction to Neural Networks: Johns Hopkins University
  • Foundations of Machine Learning: Coursera
  • Generative AI for Customer Support: IBM
  • Machine Learning for Data Analysis: Wesleyan University
  • Visual Perception: Columbia University
  • Convolutional Neural Networks: DeepLearning.AI
  • Features and Boundaries: Columbia University
  • Advanced Deep Learning Techniques for Computer Vision: MathWorks
  • Introduction to Image Processing: MathWorks
  • Machine Learning for Computer Vision: MathWorks

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