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  • Regularization Methods


Results for "regularization methods"


  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning: PCA

    Skills you'll gain: Dimensionality Reduction, NumPy, Data Preprocessing, Unsupervised Learning, Feature Engineering, Jupyter, Statistics, Linear Algebra, Python Programming, Advanced Mathematics, Calculus

    4
    Rating, 4 out of 5 stars
    ·
    3.2K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free
    Free
    C

    Coursera

    Tidymodels in R: Building tidy machine learning models

    Skills you'll gain: Tidyverse (R Package), Model Evaluation, Data Visualization, Clinical Data Management, Data Preprocessing, Data Manipulation, Predictive Modeling, R Programming, Predictive Analytics, Data Pipelines, Feature Engineering, Applied Machine Learning, Machine Learning, Random Forest Algorithm, Performance Tuning, Logistic Regression

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Preview
    Preview
    N

    National Taiwan University

    機器學習技法 (Machine Learning Techniques)

    Skills you'll gain: Feature Engineering, Deep Learning, Supervised Learning, Regression Analysis, Statistical Machine Learning, Random Forest Algorithm, Decision Tree Learning, Artificial Neural Networks, Machine Learning Algorithms, Classification Algorithms, Dimensionality Reduction, Transfer Learning, Machine Learning, Embeddings, Model Evaluation, Logistic Regression

    4.9
    Rating, 4.9 out of 5 stars
    ·
    35 reviews

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    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, Data Modeling, Data Analysis, Logistic Regression, Descriptive Analytics, Forecasting, Machine Learning, Model Evaluation, Classification Algorithms, Unsupervised Learning, Statistical Analysis

    4.5
    Rating, 4.5 out of 5 stars
    ·
    73 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free
    Free
    É

    École normale supérieure

    Approximation Algorithms Part II

    Skills you'll gain: Theoretical Computer Science, Combinatorics, Algorithms, Advanced Mathematics, Linear Algebra, Mathematical Modeling, Probability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    46 reviews

    Mixed · Course · 1 - 4 Weeks

  • 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
    J

    Johns Hopkins University

    Regression Models

    Skills you'll gain: Regression Analysis, Statistical Analysis, Statistical Modeling, Logistic Regression, Data Analysis, Model Evaluation, Probability & Statistics, Statistical Inference

    4.4
    Rating, 4.4 out of 5 stars
    ·
    3.4K reviews

    Mixed · Course · 1 - 4 Weeks

  • C

    Coursera

    Linear Regression with Python

    Skills you'll gain: Regression Analysis, NumPy, Supervised Learning, Machine Learning Algorithms, Machine Learning, Predictive Modeling, Deep Learning, Data Science, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    438 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    M

    MathWorks

    Image Segmentation, Filtering, and Region Analysis

    Skills you'll gain: Image Analysis, Image Quality, Matlab, Computer Vision, Digital Signal Processing, Spatial Data Analysis, Medical Imaging, Spatial Analysis, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    54 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    N

    National Taiwan University

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

    Skills you'll gain: Supervised Learning, Machine Learning, Statistical Machine Learning, Model Evaluation, Logistic Regression, Theoretical Computer Science, Classification Algorithms, Mathematical Theory & Analysis, Probability & Statistics, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    937 reviews

    Beginner · 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

  • G

    Google Cloud

    Introduction to Image Generation

    Skills you'll gain: Generative AI, Model Deployment, Generative Model Architectures, Cloud Deployment, Image Analysis, Unsupervised Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    195 reviews

    Beginner · Course · 1 - 4 Weeks

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

  • Mathematics for Machine Learning: PCA: Imperial College London
  • Tidymodels in R: Building tidy machine learning models: Coursera
  • 機器學習技法 (Machine Learning Techniques): National Taiwan University
  • Predictive Modeling, Model Fitting, and Regression Analysis: University of California, Irvine
  • Approximation Algorithms Part II: École normale supérieure
  • Using R for Regression and Machine Learning in Investment: Sungkyunkwan University
  • Regression Models: Johns Hopkins University
  • Linear Regression with Python: Coursera
  • Image Segmentation, Filtering, and Region Analysis: MathWorks
  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University

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