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  • Regularization Techniques

Results for "regularization+techniques"


  • T

    The University of Chicago

    Machine Learning: Concepts and Applications

    Skills you'll gain: Keras (Neural Network Library), Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Classification Algorithms, Supervised Learning, Regression Analysis, Random Forest Algorithm, Dimensionality Reduction, Model Evaluation, Data Preprocessing, Statistical Methods, Tensorflow, Feature Engineering, Pandas (Python Package)

    3.9
    Rating, 3.9 out of 5 stars
    ·
    25 reviews

    Intermediate · Course · 1 - 3 Months

  • D

    DeepLearning.AI

    PyTorch: Techniques and Ecosystem Tools

    Skills you'll gain: Transfer Learning, Embeddings, Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Model Deployment

    5
    Rating, 5 out of 5 stars
    ·
    12 reviews

    Intermediate · Course · 1 - 4 Weeks

  • W

    Wesleyan University

    Regression Modeling in Practice

    Skills you'll gain: Regression Analysis, Logistic Regression, Statistical Methods, Statistical Analysis, Statistical Modeling, Data Analysis, Correlation Analysis, Analysis, SAS (Software), Scatter Plots, Predictive Modeling, Model Evaluation, Data Manipulation, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    274 reviews

    Mixed · Course · 1 - 4 Weeks

  • U

    University of Colorado Boulder

    Approximation Methods

    Skills you'll gain: Numerical Analysis, Engineering Calculations, Applied Mathematics, Mathematical Modeling, Physics

    Build toward a degree

    4.4
    Rating, 4.4 out of 5 stars
    ·
    14 reviews

    Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    Supervised Machine Learning: Regression

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

    4.7
    Rating, 4.7 out of 5 stars
    ·
    828 reviews

    Intermediate · Course · 1 - 3 Months

  • 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

  • J

    Johns Hopkins University

    Linear Algebra: Orthogonality and Diagonalization

    Skills you'll gain: Linear Algebra, Artificial Intelligence and Machine Learning (AI/ML), Numerical Analysis, Geometry, Applied Mathematics, Algebra, Mathematical Modeling

    4.9
    Rating, 4.9 out of 5 stars
    ·
    46 reviews

    Intermediate · Course · 1 - 4 Weeks

  • S

    Stanford University

    Divide and Conquer, Sorting and Searching, and Randomized Algorithms

    Skills you'll gain: Algorithms, Graph Theory, Data Structures, Theoretical Computer Science, Computational Thinking, Analysis, Computer Science, Probability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    5.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • M

    Microsoft

    AI and Machine Learning Algorithms and Techniques

    Skills you'll gain: Unsupervised Learning, Generative AI, Large Language Modeling, Supervised Learning, Deep Learning, LLM Application, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Predictive Modeling, Machine Learning Algorithms, Artificial Neural Networks, Feature Engineering, Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Dimensionality Reduction

    4.6
    Rating, 4.6 out of 5 stars
    ·
    62 reviews

    Intermediate · Course · 1 - 3 Months

  • E

    EDUCBA

    Linear Regression with R: Build & Optimize

    Skills you'll gain: Model Evaluation, Regression Analysis, Applied Machine Learning, Data Visualization, Statistical Modeling, Feature Engineering, Predictive Modeling, Data Analysis, R Programming, Predictive Analytics, Exploratory Data Analysis, Supervised Learning, Statistical Analysis, Correlation Analysis, Probability & Statistics, Data Manipulation, Linear Algebra, Statistical Hypothesis Testing

    Mixed · Course · 1 - 4 Weeks

  • 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

  • J

    Johns Hopkins University

    Advanced Methods in Machine Learning Applications

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Random Forest Algorithm, Decision Tree Learning, Supervised Learning, Logistic Regression, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

1…567…9

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

  • Machine Learning: Concepts and Applications: The University of Chicago
  • PyTorch: Techniques and Ecosystem Tools: DeepLearning.AI
  • Regression Modeling in Practice: Wesleyan University
  • Approximation Methods: University of Colorado Boulder
  • Supervised Machine Learning: Regression: IBM
  • Calculus through Data & Modelling: Techniques of Integration: Johns Hopkins University
  • Linear Algebra: Orthogonality and Diagonalization: Johns Hopkins University
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms: Stanford University
  • AI and Machine Learning Algorithms and Techniques: Microsoft
  • Linear Regression with R: Build & Optimize: EDUCBA

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