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  • Regularization Techniques

Results for "regularization+techniques"


  • 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

  • J

    Johns Hopkins University

    Mastering Neural Networks and Model Regularization

    Skills you'll gain: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Supervised Learning, Artificial Neural Networks, Model Evaluation, Decision Tree Learning, Network Planning And Design, Machine Learning, Computer Vision

    Intermediate · Course · 1 - 3 Months

  • 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, Analysis, Computer Science, Probability

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

    Intermediate · Course · 1 - 4 Weeks

  • P

    Packt

    Deep Learning and Advanced Techniques

    Skills you'll gain: Model Deployment, Transfer Learning, Keras (Neural Network Library), Deep Learning, Applied Machine Learning, Tensorflow, PyTorch (Machine Learning Library), Convolutional Neural Networks, Artificial Neural Networks, Machine Learning Methods, Application Frameworks, Model Evaluation, Performance Tuning

    Advanced · Course · 1 - 4 Weeks

  • D

    DeepLearning.AI

    Unsupervised Learning, Recommenders, Reinforcement Learning

    Skills you'll gain: Unsupervised Learning, Data Ethics, Machine Learning, Supervised Learning, Artificial Intelligence, Reinforcement Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    5.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Fundamental Neuroscience for Neuroimaging

    Skills you'll gain: Magnetic Resonance Imaging, Neurology, Medical Imaging, Diagnostic Radiology, Anatomy, Radiology, X-Ray Computed Tomography, Experimentation, Research Design, Biomedical Technology, Image Analysis, Physiology, Medical Terminology

    4.7
    Rating, 4.7 out of 5 stars
    ·
    2.3K reviews

    Beginner · Course · 1 - 4 Weeks

  • 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
    ·
    457 reviews

    Intermediate · Course · 1 - 3 Months

  • I

    IBM

    Specialized Models: Time Series and Survival Analysis

    Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Predictive Modeling, Statistical Methods, Forecasting, Data Preprocessing, Jupyter, Applied Machine Learning, Data Transformation, Model Evaluation, Pandas (Python Package), Unsupervised Learning, Dimensionality Reduction

    4.5
    Rating, 4.5 out of 5 stars
    ·
    139 reviews

    Intermediate · Course · 1 - 4 Weeks

  • I

    Illinois Tech

    Advanced Statistical Techniques for Data Science

    Skills you'll gain: Model Evaluation, Statistical Analysis, Bayesian Statistics, Data Visualization, Statistical Inference, Exploratory Data Analysis, Data Cleansing, Regression Analysis, Analytics, Data Analysis, Logistic Regression, Machine Learning, R Programming, Data Preprocessing, Statistical Modeling, Data Validation, Statistical Methods, R (Software), Data Mining, Statistical Programming

    Build toward a degree

    4.5
    Rating, 4.5 out of 5 stars
    ·
    48 reviews

    Intermediate · Specialization · 3 - 6 Months

  • C

    Coursera

    Advanced Machine Learning Techniques

    Skills you'll gain: Transfer Learning, Data Preprocessing, Hugging Face, Model Evaluation

    Intermediate · Course · 1 - 3 Months

  • 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
    ·
    55 reviews

    Beginner · Course · 1 - 4 Weeks

  • 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, Advanced Analytics, Machine Learning Methods, Amazon S3, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Model Evaluation, Statistical Analysis, MLOps (Machine Learning Operations), Predictive Analytics, Data Preprocessing, Supervised Learning, Regression Analysis

    Beginner · Course · 1 - 3 Months

1234…9

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

  • Practical Machine Learning: Foundations to Neural Networks: Dartmouth College
  • Mastering Neural Networks and Model Regularization: Johns Hopkins University
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms: Stanford University
  • Deep Learning and Advanced Techniques: Packt
  • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
  • Fundamental Neuroscience for Neuroimaging: Johns Hopkins University
  • Supervised Machine Learning: Classification: IBM
  • Specialized Models: Time Series and Survival Analysis: IBM
  • Advanced Statistical Techniques for Data Science: Illinois Tech
  • Advanced Machine Learning Techniques: Coursera

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