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  • Regularization Methods

Results for "regularization+methods"


  • Status: Preview
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    S

    Sungkyunkwan University

    Using R for Regression and Machine Learning in Investment

    Skills you'll gain: Portfolio Risk, Regression Analysis, Predictive Analytics, Predictive Modeling, Investment Management, Risk Modeling, Risk Analysis, Investments, Machine Learning Methods, R Programming, Statistical Methods, Machine Learning, Advanced Analytics, Statistical Programming, Statistical Analysis, Financial Analysis, Machine Learning Algorithms, R (Software), Applied Machine Learning, Risk Management

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Solving ML Regression Problems with AWS AutoGluon

    Skills you'll gain: AWS SageMaker, Model Evaluation, Applied Machine Learning, Model Training, Predictive Modeling, Machine Learning Software, Machine Learning, Machine Learning Methods, Machine Learning Algorithms, Amazon Web Services, Model Optimization, Regression Analysis, Data Analysis

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Reproducibility in Cancer Informatics

    Skills you'll gain: Code Review, GitHub, Git (Version Control System), Version Control, Docker (Software), Software Development Tools, Continuous Integration, Containerization, Bioinformatics, Devops Tools, Informatics, Automation, Science and Research, Data Analysis, R Programming

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    Supervised Learning Regression Classification Clustering

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Regression Analysis, Machine Learning Methods, Classification Algorithms, Machine Learning Algorithms, Machine Learning, Predictive Modeling, Decision Tree Learning, Predictive Analytics, Logistic Regression, Random Forest Algorithm

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    E

    EDUCBA

    Deep Learning with R: Build & Predict Neural Networks

    Skills you'll gain: Plot (Graphics), Statistical Visualization, R (Software), Data Visualization Software, R Programming, Scatter Plots, Regression Analysis, Statistical Programming, Predictive Modeling, Artificial Neural Networks, Data Science, Deep Learning, Model Evaluation, Descriptive Statistics, Predictive Analytics, Statistical Methods, Data Wrangling, Data Manipulation, Machine Learning Methods, Model Training

    Mixed · Course · 1 - 4 Weeks

  • P

    Packt

    Matrix Calculus for Data Science & Machine Learning

    Skills you'll gain: Model Optimization, Calculus, Machine Learning Methods, NumPy, Machine Learning Algorithms, Applied Machine Learning, Tensorflow, Python Programming, Derivatives, Development Environment

    Intermediate · Course · 1 - 3 Months

  • 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, Unsupervised Learning, Linear Algebra

    4.4
    Rating, 4.4 out of 5 stars
    ·
    190 reviews

    Mixed · Course · 1 - 3 Months

  • C

    Coursera

    Tidymodels in R: Building tidy machine learning models

    Skills you'll gain: Tidyverse (R Package), Model Evaluation, Data Visualization, Clinical Data Management, Statistical Visualization, Data Preprocessing, Model Deployment, Data Manipulation, Data Wrangling, Model Training, Predictive Modeling, Model Optimization, R Programming, Data Processing, R (Software), Ggplot2, Predictive Analytics, Data Pipelines, Machine Learning Methods, Machine Learning

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Custom Models, Layers, and Loss Functions with TensorFlow

    Skills you'll gain: Tensorflow, Deep Learning, Keras (Neural Network Library), Convolutional Neural Networks, Model Optimization, Model Training, Artificial Neural Networks, Model Evaluation

    4.9
    Rating, 4.9 out of 5 stars
    ·
    1.1K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    A

    Arizona State University

    Modern Statistical Computing and Regression Modeling in R

    Skills you'll gain: Data Storage Technologies, Probability & Statistics, Statistics, Data Store, Mathematical Software, Data Storage, Data Access, Statistical Machine Learning, Database Software, Statistical Hypothesis Testing, Data Manipulation, Data Transformation, Model Evaluation

    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, Operations Research, Graph Theory, Applied Mathematics, Model Optimization, Advanced Mathematics, Linear Algebra, Mathematical Modeling, Network Model, Probability, Probability & Statistics

    4.8
    Rating, 4.8 out of 5 stars
    ·
    46 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Linear Regression & Supervised Learning in Python

    Skills you'll gain: Model Evaluation, Exploratory Data Analysis, Regression Analysis, Model Training, Predictive Modeling, Supervised Learning, Statistical Modeling, Data Analysis, Correlation Analysis, Predictive Analytics, Applied Machine Learning, Machine Learning Methods, Statistical Analysis, Data Preprocessing, Verification And Validation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    14 reviews

    Mixed · Course · 1 - 4 Weeks

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

  • Using R for Regression and Machine Learning in Investment: Sungkyunkwan University
  • Solving ML Regression Problems with AWS AutoGluon: Coursera
  • Advanced Reproducibility in Cancer Informatics: Johns Hopkins University
  • Supervised Learning Regression Classification Clustering: Simplilearn
  • Deep Learning with R: Build & Predict Neural Networks: EDUCBA
  • Matrix Calculus for Data Science & Machine Learning: Packt
  • Matrix Factorization and Advanced Techniques: University of Minnesota
  • Tidymodels in R: Building tidy machine learning models: Coursera
  • Custom Models, Layers, and Loss Functions with TensorFlow: DeepLearning.AI
  • Modern Statistical Computing and Regression Modeling in R: Arizona State University

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