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  • Regularization Techniques

Results for "regularization+techniques"


  • Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Linear Algebra and Regression Fundamentals for Data Science

    Skills you'll gain: NumPy, Matplotlib, Linear Algebra, Pandas (Python Package), Data Manipulation, Applied Mathematics, Data Visualization, Python Programming, Data Analysis, Data Science, Regression Analysis, Data Visualization Software, Mathematics and Mathematical Modeling, Probability & Statistics, Statistics, Numerical Analysis, Mathematical Modeling, Machine Learning, Computational Logic, Logical Reasoning

    Build toward a degree

    3.7
    Rating, 3.7 out of 5 stars
    ·
    7 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Minnesota

    Matrix Factorization and Advanced Techniques

    Skills you'll gain: Machine Learning Algorithms, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Algorithms, Model Evaluation, Linear Algebra

    4.4
    Rating, 4.4 out of 5 stars
    ·
    190 reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Calculus through Data & Modelling: Techniques of Integration

    Skills you'll gain: Integral Calculus, Numerical Analysis, Calculus, Probability, Applied Mathematics, Advanced Mathematics, Geometry, Mathematical Modeling

    4.7
    Rating, 4.7 out of 5 stars
    ·
    54 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Supervised Machine Learning: Regression

    Skills you'll gain: Supervised Learning, Regression Analysis, Applied Machine Learning, Predictive Modeling, Machine Learning, Machine Learning Algorithms, Statistical Modeling, Logistic Regression, Scikit Learn (Machine Learning Library), Model Evaluation, Data Preprocessing, Feature Engineering, Statistical Analysis, Classification Algorithms

    4.7
    Rating, 4.7 out of 5 stars
    ·
    822 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Principles of fMRI 1

    Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Radiology, Research Design, Image Analysis, Experimentation, Neurology, Data Preprocessing, Science and Research, Statistical Analysis, Statistical Modeling, Statistics

    4.7
    Rating, 4.7 out of 5 stars
    ·
    849 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Fundamental Neuroscience for Neuroimaging

    Skills you'll gain: Magnetic Resonance Imaging, Neurology, Medical Imaging, Diagnostic Radiology, Anatomy, Radiology, X-Ray Computed Tomography, Experimentation, Research Design, Biomedical Technology, Image Analysis, Physiology, Medical Terminology

    4.7
    Rating, 4.7 out of 5 stars
    ·
    2.3K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    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

  • Status: Preview
    Preview
    U

    University of Minnesota

    Matrix Methods

    Skills you'll gain: Dimensionality Reduction, NumPy, Linear Algebra, Numerical Analysis, Statistical Methods, Regression Analysis, Mathematical Modeling, Applied Mathematics, Solution Design, Applied Machine Learning, Data Manipulation, Algorithms, Python Programming

    4.1
    Rating, 4.1 out of 5 stars
    ·
    249 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of Deep Learning and Neural Networks

    Skills you'll gain: Artificial Neural Networks, Deep Learning, Convolutional Neural Networks, Image Analysis, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Machine Learning Methods, Network Architecture, Artificial Intelligence, Network Model, Machine Learning, Classification Algorithms, Data Processing

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    11 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    D

    Dartmouth College

    Practical Machine Learning: Foundations to Neural Networks

    Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Classification Algorithms, Statistical Inference

    Build toward a degree

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Advanced Data Science Techniques (with AWS Integration)

    Skills you'll gain: AWS SageMaker, Unsupervised Learning, Feature Engineering, Time Series Analysis and Forecasting, Model Deployment, Cloud Deployment, Amazon Web Services, Applied Machine Learning, Advanced Analytics, Machine Learning Methods, Amazon S3, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Model Evaluation, Statistical Analysis, MLOps (Machine Learning Operations), Predictive Analytics, Data Preprocessing, Supervised Learning, Regression Analysis

    Beginner · Course · 1 - 3 Months

1…456…9

In summary, here are 10 of our most popular regularization+techniques courses

  • Linear Algebra and Regression Fundamentals for Data Science: University of Pittsburgh
  • Matrix Factorization and Advanced Techniques: University of Minnesota
  • Calculus through Data & Modelling: Techniques of Integration: Johns Hopkins University
  • Supervised Machine Learning: Regression: IBM
  • Principles of fMRI 1: Johns Hopkins University
  • Fundamental Neuroscience for Neuroimaging: Johns Hopkins University
  • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
  • Matrix Methods: University of Minnesota
  • Foundations of Deep Learning and Neural Networks: Packt
  • Foundations of Machine Learning: Coursera

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