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  • Regularization Techniques

Results for "regularization+techniques"


  • 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: Preview
    Preview
    N

    National Taiwan University

    機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

    Skills you'll gain: Supervised Learning, Machine Learning, Statistical Machine Learning, Model Evaluation, Logistic Regression, Theoretical Computer Science, Classification Algorithms, Mathematical Theory & Analysis, Probability & Statistics, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    937 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    A

    Arizona State University

    Optical and X-Ray Characterization

    Skills you'll gain: Semiconductors, Analytical Testing, Laboratory Equipment, Materials science, Laboratory Testing, Analytical Chemistry, Laboratory Techniques

    4.8
    Rating, 4.8 out of 5 stars
    ·
    32 reviews

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Scikit-Learn to Solve Regression Machine Learning Problems

    Skills you'll gain: Scikit Learn (Machine Learning Library), Predictive Modeling, Regression Analysis, Machine Learning Algorithms, Applied Machine Learning, Predictive Analytics, Python Programming, Classification Algorithms, Machine Learning, Data Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    8 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • 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

  • 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

  • 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: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Image Classification with Keras: Build & Optimize

    Skills you'll gain: Keras (Neural Network Library), Convolutional Neural Networks, Transfer Learning, Model Evaluation, Image Analysis, Computer Vision, Deep Learning, Tensorflow, Applied Machine Learning, Data Preprocessing, Jupyter, Matplotlib, Visualization (Computer Graphics)

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Linear Regression & Supervised Learning in Python

    Skills you'll gain: Model Evaluation, Exploratory Data Analysis, Regression Analysis, Predictive Modeling, Supervised Learning, Scikit Learn (Machine Learning Library), Data Analysis, Correlation Analysis, Applied Machine Learning, Scatter Plots, Statistical Analysis, Data Validation, Data Preprocessing, NumPy, Pandas (Python Package), Box Plots, Histogram

    4.6
    Rating, 4.6 out of 5 stars
    ·
    14 reviews

    Mixed · Course · 1 - 4 Weeks

  • 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

  • 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, Data Analysis, Computer Programming, Medical Imaging, Python Programming, Histogram, Algorithms

    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

  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
  • Optical and X-Ray Characterization: Arizona State University
  • Scikit-Learn to Solve Regression Machine Learning Problems: Coursera
  • Quantization in Depth: DeepLearning.AI
  • Scikit-Learn For Machine Learning Classification Problems: Coursera
  • Prediction and Control with Function Approximation: University of Alberta
  • Image Classification with Keras: Build & Optimize: EDUCBA
  • Linear Regression & Supervised Learning in Python: EDUCBA
  • Essential Causal Inference Techniques for Data Science: Coursera

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