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  • Regularization Techniques

Results for "regularization+techniques"


  • D

    DeepLearning.AI

    PyTorch: Techniques and Ecosystem Tools

    Skills you'll gain: Transfer Learning, Embeddings, Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Model Deployment

    5
    Rating, 5 out of 5 stars
    ·
    12 reviews

    Intermediate · Course · 1 - 4 Weeks

  • E

    EDUCBA

    Regression & Forecasting for Data Scientists using Python

    Skills you'll gain: Time Series Analysis and Forecasting, Exploratory Data Analysis, Model Evaluation, Feature Engineering, Data Preprocessing, Statistical Analysis, Forecasting, Regression Analysis, Python Programming, Data Analysis, Predictive Modeling, Data Science, Matplotlib, Pandas (Python Package), Scikit Learn (Machine Learning Library), Machine Learning Algorithms

    4.5
    Rating, 4.5 out of 5 stars
    ·
    43 reviews

    Intermediate · Course · 1 - 4 Weeks

  • 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

  • L

    Ludwig-Maximilians-Universität München (LMU)

    Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

    Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Engineering Calculations, Differential Equations, Applied Mathematics, Mathematical Modeling, Distributed Computing, Python Programming, Mechanics, Vibrations, Simulations

    4.8
    Rating, 4.8 out of 5 stars
    ·
    391 reviews

    Intermediate · Course · 1 - 3 Months

  • J

    Johns Hopkins University

    Neuroscience Methods

    Skills you'll gain: Research Design, Science and Research, Laboratory Research, Research Methodologies, Statistical Analysis, Data Collection, Data Analysis Software, Neurology, Psychology, Physiology, Magnetic Resonance Imaging, Electrophysiology, Image Analysis, Medical Equipment and Technology, Human Learning, Medical Imaging, Data Visualization Software, Functional Behavior Assessment, Statistical Inference

    4.6
    Rating, 4.6 out of 5 stars
    ·
    8 reviews

    Intermediate · Course · 1 - 3 Months

  • D

    Dartmouth College

    Machine Learning Fundamentals

    Skills you'll gain: Supervised Learning, Predictive Modeling, Logistic Regression, Statistical Modeling, Model Evaluation, Machine Learning, Machine Learning Algorithms, Classification Algorithms, Regression Analysis, Probability & Statistics, Linear Algebra

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • N

    National Taiwan University

    機器學習技法 (Machine Learning Techniques)

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

    4.9
    Rating, 4.9 out of 5 stars
    ·
    35 reviews

    Intermediate · Course · 3 - 6 Months

  • 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

  • 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

  • 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

  • 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

  • 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

1…678…9

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

  • PyTorch: Techniques and Ecosystem Tools: DeepLearning.AI
  • Regression & Forecasting for Data Scientists using Python: EDUCBA
  • Introduction to advanced tomography: Technical University of Denmark (DTU)
  • Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
  • Neuroscience Methods: Johns Hopkins University
  • Machine Learning Fundamentals: Dartmouth College
  • 機器學習技法 (Machine Learning Techniques): National Taiwan University
  • Data Analysis with Python Project : University of Colorado Boulder
  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
  • Advanced Machine Learning Algorithms: Fractal Analytics

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