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  • Regularization Techniques

Results for "regularization techniques"


  • N

    National Taiwan University

    機器學習技法 (Machine Learning Techniques)

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

    ★ 4.9 (35) · Intermediate · Course · 3 - 6 Months

    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • I

    IBM

    Introduction to Neural Networks and PyTorch

    Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Applied Machine Learning, Predictive Modeling, Classification Algorithms, Predictive Analytics, Model Optimization, Tensorflow, Machine Learning, Model Training, Supervised Learning, Deep Learning, Regression Analysis, Model Evaluation, Statistical Methods, Data Preprocessing, Artificial Neural Networks, Data Processing, Probability & Statistics

    ★ 4.4 (1.9K) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of Glasgow

    Machine Learning and its Applications

    Skills you'll gain: Model Training, Model Evaluation, Data Preprocessing, Machine Learning Methods, Statistical Methods, Statistical Machine Learning, Data Validation, Data Quality, Mathematical Software, Classification Algorithms, Machine Learning Algorithms

    ★ 5 (47) · Beginner · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of Colorado Boulder

    Data Analysis with Python Project

    Skills you'll gain: Classification Algorithms, Applied Machine Learning, Machine Learning Methods, Dimensionality Reduction, Data Analysis, Supervised Learning, Anomaly Detection, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Data Mining, Predictive Modeling, Model Evaluation, Regression Analysis, Decision Tree Learning, Statistical Methods, Project Planning, Logistic Regression

    ★ 5 (7) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • P

    Packt

    Foundations of Model Optimization and Deep Learning

    Skills you'll gain: Convolutional Neural Networks, Model Optimization, Model Evaluation, Keras (Neural Network Library), Image Analysis, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Computer Vision, Model Training, Dimensionality Reduction, PyTorch (Machine Learning Library), Tensorflow, Machine Learning Methods, Performance Tuning, Artificial Intelligence, Bayesian Statistics

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • J

    Johns Hopkins University

    Applied Machine Learning: Techniques and Applications

    Skills you'll gain: Computer Vision, Model Evaluation, Supervised Learning, Image Analysis, Data Preprocessing, Applied Machine Learning, Machine Learning Methods, Feature Engineering, Machine Learning Algorithms, Data Processing, Model Training, Model Optimization, Machine Learning, Data Cleansing, Scikit Learn (Machine Learning Library), Machine Learning Software, Data Integration, Data Transformation, Classification Algorithms, Dimensionality Reduction

    ★ 3.7 (12) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of London

    Applied Mathematical Methods for Computing

    Skills you'll gain: Combinatorics, Probability & Statistics, Data Analysis, Advanced Mathematics, Linear Algebra, Mathematics and Mathematical Modeling, Mathematical Theory & Analysis, Geometry, Applied Mathematics, Statistics, Statistical Analysis, Statistical Methods, Probability, Algorithms, Algebra, Descriptive Statistics

    Beginner · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • J

    Johns Hopkins University

    Linear Algebra: Orthogonality and Diagonalization

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

    ★ 4.9 (48) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • D

    Dartmouth College

    Machine Learning with Neural Networks

    Skills you'll gain: Bayesian Network, Artificial Neural Networks, Machine Learning Methods, Convolutional Neural Networks, Deep Learning, Tensorflow, Model Training, Model Optimization, Machine Learning, Applied Machine Learning, Bayesian Statistics, Machine Learning Algorithms, Model Evaluation, Network Model, Network Architecture, Algorithms, Probability Distribution

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • 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, Machine Learning Methods, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Model Optimization, Logistic Regression, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • J

    Johns Hopkins University

    Advanced Neural Network Techniques

    Skills you'll gain: Autoencoders, Recurrent Neural Networks (RNNs), Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Generative Model Architectures, Unsupervised Learning, Responsible AI, Data Ethics, Markov Model

    ★ 4 (7) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • 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, Estimation, Probability & Statistics, Geometry, Mathematical Modeling, Graphing

    ★ 4.7 (54) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1234…457

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

  • 機器學習技法 (Machine Learning Techniques): National Taiwan University
  • Introduction to Neural Networks and PyTorch: IBM
  • Machine Learning and its Applications: University of Glasgow
  • Data Analysis with Python Project : University of Colorado Boulder
  • Foundations of Model Optimization and Deep Learning: Packt
  • Applied Machine Learning: Techniques and Applications: Johns Hopkins University
  • Applied Mathematical Methods for Computing: University of London
  • Linear Algebra: Orthogonality and Diagonalization: Johns Hopkins University
  • Machine Learning with Neural Networks: Dartmouth College
  • Advanced Methods in Machine Learning Applications: Johns Hopkins University

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