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  • Regularization Techniques

Results for "regularization+techniques"


  • D

    DeepLearning.AI

    Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

    Skills you'll gain: Tensorflow, Deep Learning, Performance Tuning, Machine Learning Methods, Data Preprocessing, Artificial Neural Networks, Model Evaluation, Verification And Validation

    4.9
    Rating, 4.9 out of 5 stars
    ·
    64K reviews

    Intermediate · Course · 1 - 4 Weeks

  • U

    University of Minnesota

    Matrix Factorization and Advanced Techniques

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

    4.4
    Rating, 4.4 out of 5 stars
    ·
    190 reviews

    Mixed · Course · 1 - 3 Months

  • C

    Coursera

    Time Series Data Visualization And Analysis Techniques

    Skills you'll gain: Time Series Analysis and Forecasting, Data Visualization, Data Visualization Software, Statistical Visualization, Data Preprocessing, Box Plots, Anomaly Detection, Heat Maps, Plotly, Exploratory Data Analysis, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    19 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • 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

  • 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

  • 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

  • N

    Northeastern University

    Machine Learning for Engineers: Algorithms and Applications

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

    Intermediate · Course · 1 - 4 Weeks

  • 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

  • U

    University of Illinois Urbana-Champaign

    Advanced Deep Learning Methods for Healthcare

    Skills you'll gain: Deep Learning, Applied Machine Learning, Generative Adversarial Networks (GANs), Healthcare Project Management, Machine Learning Methods, Image Analysis, Graph Theory, Artificial Neural Networks, Convolutional Neural Networks, Health Informatics, Autoencoders, Recurrent Neural Networks (RNNs), Predictive Modeling, Unsupervised Learning, Python Programming

    3.6
    Rating, 3.6 out of 5 stars
    ·
    15 reviews

    Advanced · Course · 1 - 4 Weeks

  • D

    DeepLearning.AI

    Quantization Fundamentals with Hugging Face

    Skills you'll gain: Generative AI, Hugging Face, Large Language Modeling, Performance Tuning, Model Deployment, Transfer Learning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    15 reviews

    Beginner · 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

  • 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

1…6789

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

  • Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: DeepLearning.AI
  • Matrix Factorization and Advanced Techniques: University of Minnesota
  • Time Series Data Visualization And Analysis Techniques : Coursera
  • Deep Learning Methods for Healthcare: University of Illinois Urbana-Champaign
  • Quantization in Depth: DeepLearning.AI
  • Scikit-Learn For Machine Learning Classification Problems: Coursera
  • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
  • Statistical Learning for Engineering Part 1: Northeastern University
  • Advanced Deep Learning Methods for Healthcare: University of Illinois Urbana-Champaign
  • Quantization Fundamentals with Hugging Face: DeepLearning.AI

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