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  • Regularization Techniques

Results for "regularization+techniques"


  • Status: Free Trial
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    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

  • 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
    ·
    5.4K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    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
    ·
    45 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Principles of fMRI 1

    Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Research Design, Image Analysis, Experimentation, Neurology, Data Preprocessing, Statistical Analysis, Statistical Modeling, Statistical Inference, Statistics

    4.6
    Rating, 4.6 out of 5 stars
    ·
    848 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Regression Analysis

    Skills you'll gain: Regression Analysis, Supervised Learning, Model Evaluation, Logistic Regression, Statistical Analysis, Data Analysis, Statistical Modeling, Predictive Modeling, Machine Learning Methods, Feature Engineering, Data Preprocessing, Exploratory Data Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    9 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Neuroscience Methods

    Skills you'll gain: Research Design, Science and Research, Laboratory Research, Research Methodologies, Statistical Analysis, Data Analysis, Data Collection, Neurology, Psychology, Physiology, Magnetic Resonance Imaging, Image Analysis, Medical Equipment and Technology, Human Learning, Medical Imaging

    4.7
    Rating, 4.7 out of 5 stars
    ·
    6 reviews

    Intermediate · Course · 1 - 3 Months

  • 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)

    3.8
    Rating, 3.8 out of 5 stars
    ·
    24 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    N

    National Taiwan University

    機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

    Skills you'll gain: Machine Learning Algorithms, Model Evaluation, Classification Algorithms, Algorithms, Supervised Learning, Logistic Regression, Machine Learning, Applied Machine Learning, Data Validation, Regression Analysis, Feature Engineering, Statistical Methods, Verification And Validation

    4.9
    Rating, 4.9 out of 5 stars
    ·
    331 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Supervised Machine Learning: Regression

    Skills you'll gain: Supervised Learning, Regression Analysis, Applied Machine Learning, Predictive Modeling, Machine Learning, Machine Learning Algorithms, Statistical Modeling, Logistic Regression, Model Evaluation, Data Preprocessing, Feature Engineering, Statistical Analysis, Classification Algorithms, Test Data, Performance Metric

    4.7
    Rating, 4.7 out of 5 stars
    ·
    815 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Preview
    Preview
    S

    Simplilearn

    Introduction to Linear Regression Training

    Skills you'll gain: Predictive Analytics, Regression Analysis, Predictive Modeling, Machine Learning, Supervised Learning, Forecasting, Case Studies, Business Analytics, Statistical Modeling

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of Deep Learning and Neural Networks

    Skills you'll gain: Artificial Neural Networks, Deep Learning, Convolutional Neural Networks, Image Analysis, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Machine Learning Methods, Network Architecture, Artificial Intelligence, Network Model, Machine Learning, Classification Algorithms, Data Processing

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    T

    Technical University of Denmark (DTU)

    Introduction to advanced tomography

    Skills you'll gain: Jupyter, Medical Imaging, 3D Modeling, Image Analysis, Engineering Analysis, Finite Element Methods, Numerical Analysis, Mathematical Modeling, Materials science, Simulation and Simulation Software, Digital Signal Processing, Python Programming, Applied Mathematics

    4.7
    Rating, 4.7 out of 5 stars
    ·
    66 reviews

    Mixed · Course · 1 - 3 Months

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

  • Calculus through Data & Modelling: Techniques of Integration: Johns Hopkins University
  • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
  • Linear Algebra: Orthogonality and Diagonalization: Johns Hopkins University
  • Principles of fMRI 1: Johns Hopkins University
  • Regression Analysis: University of Colorado Boulder
  • Neuroscience Methods: Johns Hopkins University
  • Machine Learning: Concepts and Applications: The University of Chicago
  • 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations: National Taiwan University
  • Supervised Machine Learning: Regression: IBM
  • Introduction to Linear Regression Training : Simplilearn

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