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  • Regularization Techniques

Results for "regularization+techniques"


  • 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: Preview
    Preview
    N

    Northeastern University

    Statistical Learning for Engineering Part 2

    Skills you'll gain: PyTorch (Machine Learning Library), Unsupervised Learning, Reinforcement Learning, Supervised Learning, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Transfer Learning, Decision Tree Learning, Classification Algorithms, Random Forest Algorithm, Autoencoders, Predictive Modeling, Feature Engineering

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Methods in Machine Learning Applications

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Random Forest Algorithm, Decision Tree Learning, Supervised Learning, Logistic Regression, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Techniques in Data Visualization

    Skills you'll gain: Data Visualization Software, Interactive Data Visualization, Geospatial Information and Technology, Color Theory, Tree Maps, Data Storytelling, Heat Maps, Data Mapping, Text Mining, Unstructured Data, Network Analysis

    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
    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
    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: Free Trial
    Free Trial
    F

    Fractal Analytics

    Advanced Machine Learning Algorithms

    Skills you'll gain: Feature Engineering, Model Evaluation, Machine Learning Algorithms, Random Forest Algorithm, Algorithms, Supervised Learning, Applied Machine Learning, Decision Tree Learning, Predictive Modeling, Classification Algorithms, Regression Analysis, Performance Tuning

    3.8
    Rating, 3.8 out of 5 stars
    ·
    12 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Preview
    Preview
    T

    Technical University of Denmark (DTU)

    Introduction to advanced tomography

    Skills you'll gain: Jupyter, Medical Imaging, 3D Modeling, Image Analysis, Engineering Analysis, Finite Element Methods, Numerical Analysis, Mathematical Modeling, Materials science, Simulation and Simulation Software, Digital Signal Processing, Python Programming, Applied Mathematics

    4.7
    Rating, 4.7 out of 5 stars
    ·
    67 reviews

    Mixed · 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: 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

  • 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

1…6789

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

  • Quantization in Depth: DeepLearning.AI
  • Statistical Learning for Engineering Part 2: Northeastern University
  • Advanced Methods in Machine Learning Applications: Johns Hopkins University
  • Advanced Techniques in Data Visualization: Johns Hopkins University
  • Matrix Calculus for Data Science & Machine Learning: Packt
  • Data Analysis with Python Project : University of Colorado Boulder
  • Foundations of Deep Learning and Neural Networks: Packt
  • Advanced Machine Learning Algorithms: Fractal Analytics
  • Introduction to advanced tomography: Technical University of Denmark (DTU)
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera

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