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  • Regularization Techniques

Results for "regularization+techniques"


  • C

    Coursera

    Scikit-Learn For Machine Learning Classification Problems

    Skills you'll gain: Scikit Learn (Machine Learning Library), Classification Algorithms, Applied Machine Learning, Machine Learning Algorithms, Supervised Learning, Random Forest Algorithm, Machine Learning, Unsupervised Learning, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    19 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Essential Causal Inference Techniques for Data Science

    Skills you'll gain: Regression Analysis, Data Science, Machine Learning Methods, R Programming, Statistical Inference, Applied Machine Learning, Machine Learning, Statistical Methods, Advanced Analytics, Data Analysis, Predictive Modeling

    4.5
    Rating, 4.5 out of 5 stars
    ·
    39 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Data Analysis with Python Project

    Skills you'll gain: Classification Algorithms, Dimensionality Reduction, Data Analysis, Supervised Learning, Anomaly Detection, Machine Learning, Statistical Analysis, Unsupervised Learning, Data Mining, Analytics, Predictive Modeling, Model Evaluation, Regression Analysis, Exploratory Data Analysis, Project Planning, Feature Engineering

    5
    Rating, 5 out of 5 stars
    ·
    7 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Approximation Methods

    Skills you'll gain: Numerical Analysis, Engineering Calculations, Applied Mathematics, Mathematical Modeling, Physics

    Build toward a degree

    4.4
    Rating, 4.4 out of 5 stars
    ·
    14 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Illinois Urbana-Champaign

    Deep Learning Methods for Healthcare

    Skills you'll gain: Deep Learning, Convolutional Neural Networks, Autoencoders, Recurrent Neural Networks (RNNs), Image Analysis, Embeddings, Machine Learning Methods, Model Deployment, Applied Machine Learning, Artificial Neural Networks, Health Informatics, Unsupervised Learning, Model Evaluation, Medical Imaging, Python Programming

    3.9
    Rating, 3.9 out of 5 stars
    ·
    15 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Reproducibility in Cancer Informatics

    Skills you'll gain: Code Review, GitHub, Git (Version Control System), Version Control, Docker (Software), Software Development Tools, Continuous Integration, Containerization, Bioinformatics, Informatics, Automation, Data Analysis, R Programming

    Advanced · Course · 1 - 3 Months

  • 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

  • C

    Coursera

    ML Parameters Optimization: GridSearch, Bayesian, Random

    Skills you'll gain: Model Evaluation, Scikit Learn (Machine Learning Library), Regression Analysis, Performance Tuning, Applied Machine Learning, Machine Learning Methods, Machine Learning, Bayesian Statistics, Data Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    8 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Preview
    Preview
    I

    Institut Mines-Télécom

    Traitement d'images : segmentation et caractérisation

    Skills you'll gain: Image Analysis, Computer Vision, Image Quality, Data Processing, Digital Signal Processing, Data Analysis, Computer Programming, Medical Imaging, Python Programming, Histogram, Algorithms

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Linear Regression with R: Build & Optimize

    Skills you'll gain: Model Evaluation, Regression Analysis, Applied Machine Learning, Data Visualization, Statistical Modeling, Feature Engineering, Predictive Modeling, Data Analysis, R Programming, Predictive Analytics, Exploratory Data Analysis, Supervised Learning, Statistical Analysis, Correlation Analysis, Probability & Statistics, Data Manipulation, Linear Algebra, Statistical Hypothesis Testing

    Mixed · Course · 1 - 4 Weeks

  • Status: Free
    Free
    É

    École normale supérieure

    Approximation Algorithms Part II

    Skills you'll gain: Theoretical Computer Science, Combinatorics, Algorithms, Advanced Mathematics, Linear Algebra, Mathematical Modeling, Probability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    46 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Alberta

    Prediction and Control with Function Approximation

    Skills you'll gain: Reinforcement Learning, Deep Learning, Feature Engineering, Machine Learning Algorithms, Machine Learning, Supervised Learning, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution

    4.8
    Rating, 4.8 out of 5 stars
    ·
    848 reviews

    Intermediate · Course · 1 - 3 Months

1…6789

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

  • Scikit-Learn For Machine Learning Classification Problems: Coursera
  • Essential Causal Inference Techniques for Data Science: Coursera
  • Data Analysis with Python Project : University of Colorado Boulder
  • Approximation Methods: University of Colorado Boulder
  • Deep Learning Methods for Healthcare: University of Illinois Urbana-Champaign
  • Advanced Reproducibility in Cancer Informatics: Johns Hopkins University
  • Foundations of Deep Learning and Neural Networks: Packt
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • Traitement d'images : segmentation et caractérisation: Institut Mines-Télécom
  • Linear Regression with R: Build & Optimize: EDUCBA

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