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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

    Practical Machine Learning

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning Algorithms, Model Training, Machine Learning Methods, Feature Engineering, Supervised Learning, Machine Learning Software, Classification And Regression Tree (CART), Predictive Analytics, Applied Machine Learning, Data Preprocessing, R Programming, Classification Algorithms, Machine Learning, Random Forest Algorithm, Regression Analysis

    ★ 4.5 (3.3K) · Mixed · Course · 1 - 4 Weeks

  • D

    Dartmouth College

    Foundations for Machine Learning

    Skills you'll gain: Probability & Statistics, Statistical Methods, Classification Algorithms, Calculus

    Intermediate · Course · 1 - 3 Months

  • U

    University of California, Irvine

    Predictive Modeling, Model Fitting, and Regression Analysis

    Skills you'll gain: Predictive Modeling, Predictive Analytics, Regression Analysis, Decision Tree Learning, Supervised Learning, Analytics, Logistic Regression, Descriptive Analytics, Model Training, Machine Learning, Model Evaluation, Classification Algorithms, Unsupervised Learning

    ★ 4.5 (75) · Intermediate · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Foundations of Neural Networks

    Skills you'll gain: Responsible AI, Autoencoders, Model Training, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Model Optimization, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Generative Model Architectures, Debugging, Machine Learning Methods, Artificial Intelligence, Image Analysis, Unsupervised Learning

    ★ 4.5 (24) · Intermediate · Specialization · 3 - 6 Months

  • I

    Imperial College London

    Mathematics for Machine Learning

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

    ★ 4.6 (15K) · Beginner · Specialization · 3 - 6 Months

    Category: Top AI Program
    Top AI Program
  • J

    Johns Hopkins University

    Machine Learning and Emerging Technologies in Cybersecurity

    Skills you'll gain: Model Evaluation, Intrusion Detection and Prevention, Threat Detection, Computer Security Incident Management, Cybersecurity, Model Training, Incident Response, Machine Learning Methods, Anomaly Detection, Applied Machine Learning, Continuous Monitoring, AI Security, Cryptographic Protocols, Network Security, Machine Learning Algorithms, Machine Learning, Predictive Modeling, Network Architecture, Unsupervised Learning, Supervised Learning

    Intermediate · Course · 1 - 3 Months

  • A

    Arizona State University

    Optical and X-Ray Characterization

    Skills you'll gain: Semiconductors, Engineering, Scientific, and Technical Instruments, Analytical Testing, Laboratory Equipment, Materials science, Laboratory Testing, Analytical Chemistry, Structural Analysis, Laboratory Techniques

    ★ 4.8 (33) · Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Train ML Models

    Skills you'll gain: Random Forest Algorithm, Model Evaluation, Feature Engineering, Model Training, Applied Machine Learning, Supervised Learning, Geospatial Mapping, Predictive Modeling, Image Analysis, Verification And Validation, Data Science, Environmental Engineering

    Beginner · Course · 1 - 4 Weeks

  • M

    MathWorks

    Medical Image Processing

    Skills you'll gain: Medical Imaging, Magnetic Resonance Imaging, Image Analysis, Data Import/Export, Image Quality, Matlab, Deep Learning, Software Visualization

    ★ 4.7 (28) · Beginner · Course · 1 - 4 Weeks

  • J

    John Wiley & Sons

    Data Processing, Machine Learning, and Model Evaluation

    Skills you'll gain: Data Preprocessing, Model Evaluation, Data Processing, Model Deployment, Data Transformation, MLOps (Machine Learning Operations), Unsupervised Learning, Data Cleansing, Predictive Modeling, Model Training, Data Science, Data Analysis, Applied Machine Learning, Model Optimization, Technical Communication, Supervised Learning, Machine Learning, Artificial Neural Networks

    Intermediate · Course · 1 - 4 Weeks

  • L

    LearnQuest

    Neural Networks and Random Forests

    Skills you'll gain: Model Evaluation, Random Forest Algorithm, Model Optimization, Keras (Neural Network Library), Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Decision Tree Learning, Machine Learning Methods, Applied Machine Learning, Predictive Modeling, Fine-tuning, Scikit Learn (Machine Learning Library), Regression Analysis, Classification Algorithms, Python Programming

    ★ 3.2 (18) · Intermediate · Course · 1 - 4 Weeks

  • G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

    ★ 4.8 (623) · Advanced · Course · 1 - 3 Months

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

  • Practical Machine Learning: Johns Hopkins University
  • Foundations for Machine Learning: Dartmouth College
  • Predictive Modeling, Model Fitting, and Regression Analysis: University of California, Irvine
  • Foundations of Neural Networks: Johns Hopkins University
  • Mathematics for Machine Learning: Imperial College London
  • Machine Learning and Emerging Technologies in Cybersecurity: Johns Hopkins University
  • Optical and X-Ray Characterization: Arizona State University
  • Train ML Models: Coursera
  • Medical Image Processing: MathWorks
  • Data Processing, Machine Learning, and Model Evaluation: John Wiley & Sons

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