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  • Regularization Techniques

Results for "regularization+techniques"


  • 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: 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

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Calculus through Data & Modelling: Techniques of Integration

    Skills you'll gain: Integral Calculus, Numerical Analysis, Calculus, Probability, Applied Mathematics, Advanced Mathematics, Geometry, Mathematical Modeling

    4.7
    Rating, 4.7 out of 5 stars
    ·
    54 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    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

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Linear Regression with R: Build & Optimize

    Skills you'll gain: Model Evaluation, Regression Analysis, Applied Machine Learning, Data Visualization, Statistical Modeling, Feature Engineering, Predictive Modeling, Data Analysis, R Programming, Predictive Analytics, Exploratory Data Analysis, Supervised Learning, Statistical Analysis, Correlation Analysis, Probability & Statistics, Data Manipulation, Linear Algebra, Statistical Hypothesis Testing

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    Supervised Learning Regression Classification Clustering

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Regression Analysis, Classification Algorithms, Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Decision Tree Learning, Predictive Analytics, Logistic Regression, Random Forest Algorithm, Bayesian Statistics

    Beginner · Course · 1 - 4 Weeks

  • 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

  • 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 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
    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

  • 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
    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

1…6789

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

  • Essential Causal Inference Techniques for Data Science: Coursera
  • Linear Regression & Supervised Learning in Python: EDUCBA
  • Calculus through Data & Modelling: Techniques of Integration: Johns Hopkins University
  • Neuroscience Methods: Johns Hopkins University
  • Linear Regression with R: Build & Optimize: EDUCBA
  • Supervised Learning Regression Classification Clustering: Simplilearn
  • Advanced Techniques in Data Visualization: Johns Hopkins University
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • Data Analysis with Python Project : University of Colorado Boulder
  • Approximation Algorithms Part II: École normale supérieure

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