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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

  • N

    National Taiwan University

    機器學習技法 (Machine Learning Techniques)

    Skills you'll gain: Feature Engineering, Supervised Learning, Machine Learning Algorithms, Random Forest Algorithm, Deep Learning, Classification Algorithms, Machine Learning, Applied Machine Learning, Decision Tree Learning, Artificial Neural Networks, Model Evaluation, Dimensionality Reduction, Logistic Regression, Regression Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    35 reviews

    Intermediate · Course · 3 - 6 Months

  • 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

    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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

1…678…9

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

  • Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: DeepLearning.AI
  • 機器學習技法 (Machine Learning Techniques): National Taiwan University
  • Quantization Fundamentals with Hugging Face: DeepLearning.AI
  • Scikit-Learn to Solve Regression Machine Learning Problems: Coursera
  • Machine Learning with Neural Networks: Dartmouth College
  • Time Series Data Visualization And Analysis Techniques : Coursera
  • Quantization in Depth: DeepLearning.AI
  • Advanced Machine Learning Algorithms: Fractal Analytics
  • Scikit-Learn For Machine Learning Classification Problems: Coursera
  • Matrix Calculus for Data Science & Machine Learning: Packt

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