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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


  • C

    Coursera

    Process Images & Extract Motion Features

    Skills you'll gain: Data Preprocessing, Computer Vision, Image Analysis, Real Time Data, Convolutional Neural Networks, Data Transformation, NumPy

    Intermediate · Course · 1 - 4 Weeks

  • M

    MathWorks

    Introduction to Deep Learning for Computer Vision

    Skills you'll gain: Model Evaluation, Computer Vision, Convolutional Neural Networks, Image Analysis, Transfer Learning, Matlab, Artificial Neural Networks, Deep Learning, Applied Machine Learning, Classification Algorithms, Performance Tuning

    4.9
    Rating, 4.9 out of 5 stars
    ·
    19 reviews

    Beginner · Course · 1 - 4 Weeks

  • E

    EDUCBA

    Analyze Fraud Using Data Analytics and R

    Skills you'll gain: Fraud detection, Anomaly Detection, R Programming, Credit Risk, Applied Machine Learning, Analytical Skills, Machine Learning Methods, Threat Detection, Unsupervised Learning, Risk Analysis, Advanced Analytics, Analytics, Predictive Analytics, Data-Driven Decision-Making, Supervised Learning, Big Data

    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
    ·
    205 reviews

    Beginner · Course · 1 - 4 Weeks

  • 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

  • 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

  • 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

  • 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

  • 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

  • U

    University of Colorado Boulder

    Deep Learning Applications for Computer Vision

    Skills you'll gain: Computer Vision, Convolutional Neural Networks, Image Analysis, Tensorflow, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Machine Learning, Model Evaluation, Performance Tuning, Classification Algorithms

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    88 reviews

    Intermediate · Course · 1 - 3 Months

  • M

    MathWorks

    Machine Learning for Computer Vision

    Skills you'll gain: Computer Vision, Model Evaluation, Image Analysis, Matlab, Machine Learning Methods, Data Preprocessing, Machine Learning, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Algorithms, Deep Learning, Data Validation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    23 reviews

    Beginner · Course · 1 - 4 Weeks

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

  • Process Images & Extract Motion Features: Coursera
  • Introduction to Deep Learning for Computer Vision: MathWorks
  • Analyze Fraud Using Data Analytics and R: EDUCBA
  • Introduction to Image Processing: MathWorks
  • Face Recognition with Keras: Detect & Classify: EDUCBA
  • Convolutional Neural Networks: DeepLearning.AI
  • Machine Learning for Data Analysis: Wesleyan University
  • Visual Perception: Columbia University
  • Advanced Deep Learning Techniques for Computer Vision: MathWorks
  • Introduction to Machine Learning: Duke University

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