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  • Regularization Techniques


Results for "regularization techniques"


  • Status: Preview
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    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
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    N

    National Taiwan University

    機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

    Skills you'll gain: Supervised Learning, Statistical Machine Learning, Machine Learning, Applied Mathematics, Classification Algorithms, Theoretical Computer Science, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Algorithms, Probability & Statistics

    4.9
    Rating, 4.9 out of 5 stars
    ·
    937 reviews

    Beginner · Course · 1 - 3 Months

  • C

    Coursera

    Scikit-Learn For Machine Learning Classification Problems

    Skills you'll gain: Scikit Learn (Machine Learning Library), Classification Algorithms, Applied Machine Learning, Machine Learning Algorithms, Supervised Learning, Random Forest Algorithm, Machine Learning, Unsupervised Learning, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    19 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Introduction to Reproducibility in Cancer Informatics

    Skills you'll gain: Package and Software Management, Code Review, Open Source Technology, GitHub, Scientific Methods, Bioinformatics, Technical Documentation, Informatics, Clinical Informatics, R (Software), Data Analysis, Programming Principles, R Programming, Version Control, Integrated Development Environments

    Intermediate · Course · 1 - 3 Months

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

    Dartmouth College

    Foundations for Machine Learning

    Skills you'll gain: Classification Algorithms

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning: Linear Algebra

    Skills you'll gain: Linear Algebra, NumPy, Applied Mathematics, Machine Learning Algorithms, Jupyter, Algorithms, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    13K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    H

    Howard University

    Building Regression Models with Linear Algebra

    Skills you'll gain: Regression Analysis, Predictive Modeling, Statistical Modeling, Applied Mathematics, Machine Learning Methods, Linear Algebra, Model Evaluation, Statistical Analysis, Data Manipulation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    6 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    SAS

    Modeling Time Series and Sequential Data

    Skills you'll gain: Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), SAS (Software), Forecasting, Regression Analysis, Machine Learning Methods, Statistical Analysis, Advanced Analytics, Statistical Methods, Predictive Modeling, Statistical Modeling, Bayesian Statistics, Model Evaluation

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    S

    Sungkyunkwan University

    Using R for Regression and Machine Learning in Investment

    Skills you'll gain: Regression Analysis, Predictive Analytics, Predictive Modeling, Investment Management, Risk Analysis, Investments, R Programming, Machine Learning, Statistical Analysis, Financial Analysis, Logistic Regression, Financial Data, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    T

    The Hong Kong University of Science and Technology

    Numerical Methods for Engineers

    Skills you'll gain: Matlab, Engineering Calculations, Numerical Analysis, Mathematical Software, Engineering Analysis, Linear Algebra, Differential Equations, Applied Mathematics, Mathematical Modeling, Simulation and Simulation Software, Computational Thinking, Estimation, Integral Calculus, Scripting, Simulations, Calculus, Scientific Visualization, Programming Principles, Plot (Graphics), Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    422 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    K

    Korea Advanced Institute of Science and Technology(KAIST)

    MRI Fundamentals

    Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Image Quality, Digital Signal Processing, Medical Equipment and Technology

    4.5
    Rating, 4.5 out of 5 stars
    ·
    470 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Generalized Linear Models and Nonparametric Regression

    Skills you'll gain: Statistical Modeling, R Programming, Data Analysis, Data Ethics, Statistical Methods, Regression Analysis, Predictive Modeling, Mathematical Modeling, Machine Learning, Logistic Regression, Statistical Inference, Model Evaluation, Probability Distribution, Linear Algebra, Calculus

    Build toward a degree

    4.3
    Rating, 4.3 out of 5 stars
    ·
    21 reviews

    Intermediate · Course · 1 - 4 Weeks

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

  • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
  • Scikit-Learn For Machine Learning Classification Problems: Coursera
  • Introduction to Reproducibility in Cancer Informatics: Johns Hopkins University
  • Foundations for Machine Learning: Dartmouth College
  • Mathematics for Machine Learning: Linear Algebra: Imperial College London
  • Building Regression Models with Linear Algebra: Howard University
  • Modeling Time Series and Sequential Data: SAS
  • Using R for Regression and Machine Learning in Investment: Sungkyunkwan University
  • Numerical Methods for Engineers: The Hong Kong University of Science and Technology

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