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  • Regularization Techniques

Results for "regularization+techniques"


  • U

    University of Pittsburgh

    Linear Algebra and Regression Fundamentals for Data Science

    Skills you'll gain: NumPy, Matplotlib, Plot (Graphics), Linear Algebra, Pandas (Python Package), Data Manipulation, Applied Mathematics, Python Programming, Data Analysis, Data Science, Mathematical Software, Regression Analysis, Data Visualization Software, Mathematics and Mathematical Modeling, Probability & Statistics, Numerical Analysis, Mathematical Modeling, Machine Learning, Computational Logic, Logical Reasoning

    ★ 3.9 (8) · Beginner · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • J

    Johns Hopkins University

    Data Science: Foundations using R

    Skills you'll gain: Rmarkdown, Exploratory Data Analysis, R (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Wrangling, Data Visualization, Data Processing, Plot (Graphics), Statistical Programming, Statistical Visualization, Ggplot2, Knitr, Data Sharing, GitHub, Machine Learning

    ★ 4.6 (48K) · Beginner · Specialization · 3 - 6 Months

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

    Microsoft

    AI and Machine Learning Algorithms and Techniques

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

    ★ 4.7 (64) · Intermediate · Course · 1 - 3 Months

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

    Johns Hopkins University

    Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors

    Skills you'll gain: Linear Algebra, Applied Mathematics, Algebra, Advanced Mathematics, Geometry, Applied Machine Learning, Markov Model

    ★ 4.8 (77) · Mixed · Course · 1 - 3 Months

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

    Johns Hopkins University

    Foundational Mathematics for AI

    Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Data Analysis, Bayesian Statistics, Artificial Intelligence, Probability, Regression Analysis, Calculus, Mathematical Software, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Model Optimization, Integral Calculus, Algebra, Machine Learning Algorithms, Dimensionality Reduction

    ★ 4.9 (10) · Beginner · Course · 1 - 3 Months

    Category: Preview
    Preview
    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, Geometry, Mathematical Modeling

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

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

    Stanford University

    Divide and Conquer, Sorting and Searching, and Randomized Algorithms

    Skills you'll gain: Algorithms, Graph Theory, Theoretical Computer Science, Computational Thinking, Mathematical Theory & Analysis, Analysis, Computer Science, Probability & Statistics, Probability, Design Strategies

    ★ 4.8 (5.3K) · Intermediate · Course · 1 - 4 Weeks

    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), Numerical Analysis, Geometry, Applied Mathematics, Algebra, Mathematical Modeling

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

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

    University of Pittsburgh

    Statistics and Calculus Methods for Data Analysis

    Skills you'll gain: Statistical Analysis, Statistical Methods, Statistical Modeling, Predictive Modeling, Data Analysis, Statistics, Integral Calculus, Probability & Statistics, Data Science, Probability Distribution, Calculus, Mathematics and Mathematical Modeling, Applied Mathematics, Derivatives, Probability, Mathematical Modeling, Machine Learning, Algorithms

    Beginner · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • I

    Imperial College London

    Mathematics for Machine Learning: PCA

    Skills you'll gain: Dimensionality Reduction, NumPy, Data Preprocessing, Unsupervised Learning, Feature Engineering, Jupyter, Statistics, Linear Algebra, Python Programming, Advanced Mathematics, Calculus

    ★ 4 (3.2K) · Intermediate · Course · 1 - 4 Weeks

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

    IBM

    Supervised Machine Learning: Regression

    Skills you'll gain: Supervised Learning, Regression Analysis, Applied Machine Learning, Predictive Modeling, Machine Learning Methods, Model Training, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Statistical Modeling, Model Evaluation, Data Preprocessing, Feature Engineering, Model Optimization, Statistical Analysis, Statistical Methods, Classification Algorithms, Data Presentation

    ★ 4.7 (833) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1234…9

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

  • Linear Algebra and Regression Fundamentals for Data Science: University of Pittsburgh
  • Data Science: Foundations using R: Johns Hopkins University
  • AI and Machine Learning Algorithms and Techniques: Microsoft
  • Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors: Johns Hopkins University
  • Foundational Mathematics for AI: Johns Hopkins University
  • Advanced Neural Network Techniques: Johns Hopkins University
  • Calculus through Data & Modelling: Techniques of Integration: Johns Hopkins University
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms: Stanford University
  • Linear Algebra: Orthogonality and Diagonalization: Johns Hopkins University
  • Statistics and Calculus Methods for Data Analysis: University of Pittsburgh

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