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  • Regularization Techniques


Results for "regularization+techniques"


  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Linear Algebra for Machine Learning and Data Science

    Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Data Preprocessing, Machine Learning Methods, Advanced Mathematics, Data Manipulation, Applied Mathematics, Mathematical Modeling, Machine Learning, Python Programming, Algebra

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Packt

    Deep Learning and Advanced Techniques

    Skills you'll gain: Model Deployment, Transfer Learning, Keras (Neural Network Library), Deep Learning, Applied Machine Learning, Tensorflow, PyTorch (Machine Learning Library), Convolutional Neural Networks, Artificial Neural Networks, Machine Learning Methods, Application Frameworks, Model Evaluation, Performance Tuning

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Mastering Neural Networks and Model Regularization

    Skills you'll gain: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Supervised Learning, Artificial Neural Networks, Model Evaluation, Decision Tree Learning, Network Planning And Design, Machine Learning, Computer Vision

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

    Skills you'll gain: Tensorflow, Deep Learning, Performance Tuning, Machine Learning Methods, Data Preprocessing, Artificial Neural Networks, Model Evaluation, Verification And Validation

    4.9
    Rating, 4.9 out of 5 stars
    ·
    64K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Supervised Machine Learning: Classification

    Skills you'll gain: Classification Algorithms, Supervised Learning, Model Evaluation, Data Preprocessing, Logistic Regression, Decision Tree Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Cleansing, Machine Learning, Feature Engineering, Random Forest Algorithm, Sampling (Statistics), Performance Metric

    4.8
    Rating, 4.8 out of 5 stars
    ·
    451 reviews

    Intermediate · Course · 1 - 3 Months

  • 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: Preview
    Preview
    U

    University of Michigan

    The Finite Element Method for Problems in Physics

    Skills you'll gain: Finite Element Methods, Engineering Analysis, Mathematical Software, Numerical Analysis, Mathematical Modeling, Advanced Mathematics, C++ (Programming Language)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    562 reviews

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Unsupervised Learning, Recommenders, Reinforcement Learning

    Skills you'll gain: Unsupervised Learning, Data Ethics, Machine Learning, Supervised Learning, Artificial Intelligence, Reinforcement Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    5.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    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

  • Status: Free Trial
    Free Trial
    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

  • Status: Free Trial
    Free Trial
    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

    4.7
    Rating, 4.7 out of 5 stars
    ·
    60 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    L

    Ludwig-Maximilians-Universität München (LMU)

    Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

    Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Engineering Calculations, Differential Equations, Applied Mathematics, Mathematical Modeling, Distributed Computing, Python Programming, Mechanics, Vibrations, Simulations

    4.8
    Rating, 4.8 out of 5 stars
    ·
    391 reviews

    Intermediate · Course · 1 - 3 Months

1234…9

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

  • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
  • Deep Learning and Advanced Techniques: Packt
  • Mastering Neural Networks and Model Regularization: Johns Hopkins University
  • Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: DeepLearning.AI
  • Supervised Machine Learning: Classification: IBM
  • Matrix Methods: University of Minnesota
  • The Finite Element Method for Problems in Physics: University of Michigan
  • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
  • Machine Learning: Concepts and Applications: The University of Chicago
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms: Stanford University

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