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  • Regularization Techniques

Results for "regularization+techniques"


  • Status: Free Trial
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    I

    Illinois Tech

    Introduction to Data Science Techniques

    Skills you'll gain: Statistical Analysis, Time Series Analysis and Forecasting, Data Analysis, Model Evaluation, Data Visualization, Exploratory Data Analysis, Statistical Programming, Statistical Machine Learning, Statistical Modeling, Data Cleansing, Analytics, Regression Analysis, R Programming, Statistical Software, Forecasting, Data Preprocessing, Bayesian Statistics, Supervised Learning, Statistical Inference, Machine Learning

    Build toward a degree

    4.3
    Rating, 4.3 out of 5 stars
    ·
    21 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning: Linear Algebra

    Skills you'll gain: Linear Algebra, NumPy, Applied Mathematics, Machine Learning Algorithms, Jupyter, Algorithms, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    13K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors

    Skills you'll gain: Linear Algebra, Applied Mathematics, Algebra, Advanced Mathematics, Geometry, Data Transformation, Applied Machine Learning, Dimensionality Reduction, Markov Model, Probability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    76 reviews

    Mixed · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    D

    Dartmouth College

    Practical Machine Learning: Foundations to Neural Networks

    Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Classification Algorithms, Statistical Inference

    Build toward a degree

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    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), Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Data Ethics, Markov Model

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    M

    MathWorks

    Advanced Deep Learning Techniques for Computer Vision

    Skills you'll gain: Model Deployment, Anomaly Detection, Image Analysis, Computer Vision, Matlab, Deep Learning, Applied Machine Learning, PyTorch (Machine Learning Library), Transfer Learning, Data Synthesis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    15 reviews

    Beginner · 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, Radiology, Research Design, Image Analysis, Experimentation, Neurology, Data Preprocessing, Science and Research, Statistical Analysis, Statistical Modeling, Statistics

    4.7
    Rating, 4.7 out of 5 stars
    ·
    849 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Advanced Data Science Techniques (with AWS Integration)

    Skills you'll gain: AWS SageMaker, Unsupervised Learning, Feature Engineering, Time Series Analysis and Forecasting, Model Deployment, Cloud Deployment, Amazon Web Services, Applied Machine Learning, Amazon Redshift, Machine Learning Methods, Amazon S3, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Model Evaluation, Forecasting, MLOps (Machine Learning Operations), Predictive Analytics, Data Preprocessing, Supervised Learning, Dimensionality Reduction

    Beginner · Course · 1 - 3 Months

  • 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
    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
    M

    MathWorks

    Image Segmentation, Filtering, and Region Analysis

    Skills you'll gain: Image Analysis, Image Quality, Matlab, Computer Vision, Digital Signal Processing, Spatial Data Analysis, Medical Imaging, Spatial Analysis, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    54 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    N

    Northeastern University

    Foundations of Statistical Learning & Algorithms

    Skills you'll gain: Model Evaluation, Linear Algebra, Statistical Machine Learning, Probability, Bayesian Statistics, Probability Distribution, Mathematical Modeling, Machine Learning, Applied Mathematics, Statistical Inference, Dimensionality Reduction, Algebra

    Mixed · Course · 1 - 4 Weeks

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

  • Introduction to Data Science Techniques: Illinois Tech
  • Mathematics for Machine Learning: Linear Algebra: Imperial College London
  • Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors: Johns Hopkins University
  • Practical Machine Learning: Foundations to Neural Networks: Dartmouth College
  • Advanced Neural Network Techniques: Johns Hopkins University
  • Advanced Deep Learning Techniques for Computer Vision: MathWorks
  • Principles of fMRI 1: Johns Hopkins University
  • Advanced Data Science Techniques (with AWS Integration): Coursera
  • Supervised Machine Learning: Classification: IBM
  • Machine Learning: Concepts and Applications: The University of Chicago

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