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  • Regularization Techniques

Results for "regularization+techniques"


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

    DeepLearning.AI

    PyTorch: Techniques and Ecosystem Tools

    Skills you'll gain: Transfer Learning, Embeddings, Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Model Deployment

    5
    Rating, 5 out of 5 stars
    ·
    14 reviews

    Intermediate · Course · 1 - 4 Weeks

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

    Dartmouth College

    Machine Learning with Neural Networks

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

    Build toward a degree

    Intermediate · 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

  • Status: Preview
    Preview
    N

    Northeastern University

    Machine Learning with Small Data Part 2

    Skills you'll gain: Generative AI, Transfer Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Applied Machine Learning, Small Data, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Machine Learning Methods, Computer Graphics, Machine Learning, Artificial Neural Networks, Image Analysis, Machine Learning Algorithms, Data Synthesis, Simulation and Simulation Software, Computer Vision, Simulations, 3D Modeling

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    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, Feature Engineering, Machine Learning Algorithms, Data Processing, Machine Learning, Data Cleansing, Scikit Learn (Machine Learning Library), Data Integration, Data Transformation, Data Manipulation, Classification Algorithms

    3.7
    Rating, 3.7 out of 5 stars
    ·
    12 reviews

    Intermediate · Course · 1 - 4 Weeks

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

    Dartmouth College

    Foundations for Machine Learning

    Skills you'll gain: Classification Algorithms

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    Machine Learning Models in Science

    Skills you'll gain: Data Preprocessing, Applied Machine Learning, Dimensionality Reduction, Data Cleansing, Scikit Learn (Machine Learning Library), Data Transformation, Artificial Neural Networks, Random Forest Algorithm, Machine Learning, Unsupervised Learning, Supervised Learning, Classification Algorithms, Predictive Modeling, Python Programming

    4.1
    Rating, 4.1 out of 5 stars
    ·
    14 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    N

    Northeastern University

    Statistical Learning for Engineering Part 1

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Machine Learning Software, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Logistic Regression, Unstructured Data, Model Evaluation, Dimensionality Reduction

    Intermediate · Course · 1 - 3 Months

  • Status: Free
    Free
    D

    DeepLearning.AI

    Quantization in Depth

    Skills you'll gain: PyTorch (Machine Learning Library), Model Evaluation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    6 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Regression Analysis

    Skills you'll gain: Regression Analysis, Supervised Learning, Model Evaluation, Logistic Regression, Statistical Analysis, Data Analysis, Statistical Modeling, Predictive Modeling, Machine Learning Methods, Feature Engineering, Data Preprocessing, Exploratory Data Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    10 reviews

    Intermediate · Course · 1 - 3 Months

  • P

    Packt

    Matrix Calculus for Data Science & Machine Learning

    Skills you'll gain: Calculus, Applied Mathematics, NumPy, Machine Learning Algorithms, Data Science, Tensorflow, Python Programming, Derivatives, Algorithms, Development Environment

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    W

    Wesleyan University

    Regression Modeling in Practice

    Skills you'll gain: Regression Analysis, Logistic Regression, Statistical Methods, Statistical Analysis, Statistical Modeling, Data Analysis, Correlation Analysis, Analysis, SAS (Software), Scatter Plots, Predictive Modeling, Model Evaluation, Data Manipulation, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    274 reviews

    Mixed · Course · 1 - 4 Weeks

1…678…9

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

  • PyTorch: Techniques and Ecosystem Tools: DeepLearning.AI
  • Machine Learning with Neural Networks: Dartmouth College
  • Foundations of Deep Learning and Neural Networks: Packt
  • Machine Learning with Small Data Part 2: Northeastern University
  • Applied Machine Learning: Techniques and Applications: Johns Hopkins University
  • Foundations for Machine Learning: Dartmouth College
  • Machine Learning Models in Science: LearnQuest
  • Statistical Learning for Engineering Part 1: Northeastern University
  • Quantization in Depth: DeepLearning.AI
  • Regression Analysis: University of Colorado Boulder

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