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  • Regularization Techniques

Results for "regularization+techniques"


  • 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), Model Training, Tensorflow, Network Architecture, Artificial Intelligence, Model Optimization, Machine Learning, Linear Algebra

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    U

    University of Michigan

    The Finite Element Method for Problems in Physics

    Skills you'll gain: Finite Element Methods, Engineering Analysis, Mathematical Software, Numerical Analysis, Mathematical Modeling, C++ (Programming Language), Structural Engineering, Computer Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    564 reviews

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Divide and Conquer, Sorting and Searching, and Randomized Algorithms

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

    4.8
    Rating, 4.8 out of 5 stars
    ·
    5.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Minnesota

    Matrix Factorization and Advanced Techniques

    Skills you'll gain: Machine Learning Algorithms, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Algorithms, Unsupervised Learning, Linear Algebra

    4.4
    Rating, 4.4 out of 5 stars
    ·
    190 reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    PyTorch: Techniques and Ecosystem Tools

    Skills you'll gain: Hugging Face, Model Optimization, Fine-tuning, Transfer Learning, Model Training, Embeddings, Data Preprocessing

    5
    Rating, 5 out of 5 stars
    ·
    15 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    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

  • Status: Free Trial
    Free Trial
    U

    University of Illinois Urbana-Champaign

    Advanced Deep Learning Methods for Healthcare

    Skills you'll gain: Deep Learning, Generative AI, Generative Model Architectures, Applied Machine Learning, Machine Learning Methods, Graph Theory, Network Analysis, Artificial Neural Networks, Network Model, Health Informatics, Laboratory Experience, Autoencoders, Predictive Modeling, Unsupervised Learning, Data Synthesis

    3.6
    Rating, 3.6 out of 5 stars
    ·
    15 reviews

    Advanced · Course · 1 - 4 Weeks

  • 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, Systems Of Measurement, Data Analysis, Computer Programming, Medical Imaging, Python Programming, Histogram, Algorithms, Machine Learning Algorithms, Applied Mathematics

    Intermediate · Course · 1 - 3 Months

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

    Dartmouth College

    Machine Learning Fundamentals

    Skills you'll gain: Supervised Learning, Predictive Modeling, Logistic Regression, Statistical Modeling, Model Evaluation, Statistical Machine Learning, Machine Learning Methods, Applied Machine Learning, Machine Learning, Generative Model Architectures, Machine Learning Algorithms, Classification Algorithms, Model Optimization, Regression Analysis, Probability & Statistics

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    F

    Fractal Analytics

    Advanced Machine Learning Algorithms

    Skills you'll gain: Feature Engineering, Model Evaluation, Machine Learning Algorithms, Model Optimization, Machine Learning Methods, Random Forest Algorithm, Advanced Analytics, Algorithms, Applied Machine Learning, Decision Tree Learning, Predictive Modeling, Data Preprocessing, Fine-tuning, Performance Tuning

    3.8
    Rating, 3.8 out of 5 stars
    ·
    12 reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Packt

    Applied Machine Learning and Model Optimization

    Skills you'll gain: Supervised Learning, Model Optimization, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Predictive Modeling, Model Training, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Data Transformation, Fine-tuning

    Advanced · Course · 1 - 3 Months

  • C

    Coursera

    Scikit-Learn For Machine Learning Classification Problems

    Skills you'll gain: Scikit Learn (Machine Learning Library), Classification Algorithms, Applied Machine Learning, Model Training, Machine Learning Algorithms, Predictive Modeling, 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

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

  • Foundations of Deep Learning and Neural Networks: Packt
  • The Finite Element Method for Problems in Physics: University of Michigan
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms: Stanford University
  • Matrix Factorization and Advanced Techniques: University of Minnesota
  • PyTorch: Techniques and Ecosystem Tools: DeepLearning.AI
  • Foundations of Model Optimization and Deep Learning: Packt
  • Advanced Deep Learning Methods for Healthcare: University of Illinois Urbana-Champaign
  • Traitement d'images : segmentation et caractérisation: Institut Mines-Télécom
  • Machine Learning Fundamentals: Dartmouth College
  • Advanced Machine Learning Algorithms: Fractal Analytics

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