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  • Support Vector Machine Svm Theory And Implementation

Results for "support vector machine (svm) theory and implementation"


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    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

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    Dartmouth College

    Practical Machine Learning: Foundations to Neural Networks

    Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Classification Algorithms, Statistical Inference

    Build toward a degree

    Intermediate · Specialization · 3 - 6 Months

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    University of Colorado Boulder

    Machine Learning: Theory and Hands-on Practice with Python

    Skills you'll gain: Recurrent Neural Networks (RNNs), Vision Transformer (ViT), PyTorch (Machine Learning Library), Keras (Neural Network Library), Large Language Modeling, Natural Language Processing, Embeddings, AI Personalization, Network Model, Network Architecture, Linear Algebra

    Intermediate · Specialization · 3 - 6 Months

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    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods

    4.6
    Rating, 4.6 out of 5 stars
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    3.1K reviews

    Intermediate · Specialization · 1 - 3 Months

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    Coursera

    Improve Accuracy with ML Ensemble Methods

    Skills you'll gain: Random Forest Algorithm, Decision Tree Learning, Data Preprocessing, Applied Machine Learning, Jupyter, Classification Algorithms, Java, Sampling (Statistics), Feature Engineering, Model Evaluation, Supervised Learning, Predictive Modeling, Machine Learning, Learning Styles, Program Evaluation, Program Implementation

    Intermediate · Course · 1 - 4 Weeks

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    U

    University of Illinois Urbana-Champaign

    Data Mining

    Skills you'll gain: Data Visualization, Data Visualization Software, Text Mining, Data Presentation, Data Mining, Interactive Data Visualization, Data Storytelling, Dashboard, Tableau Software, Plot (Graphics), Natural Language Processing, Scatter Plots, Unsupervised Learning, Data Mapping, Unstructured Data, Statistical Analysis, Graphing, Predictive Analytics, Big Data, Anomaly Detection

    4.5
    Rating, 4.5 out of 5 stars
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    2.9K reviews

    Intermediate · Specialization · 3 - 6 Months

What brings you to Coursera today?

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    U

    University of Michigan

    Applied Machine Learning in Python

    Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
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    8.7K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Next level skills. New Year savings.

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    J

    Johns Hopkins University

    Statistical Methods for Computer Science

    Skills you'll gain: Network Analysis, R Programming, Statistical Analysis, Regression Analysis, Statistical Modeling, Bayesian Network, Statistical Hypothesis Testing, Statistical Programming, Data Analysis, R (Software), Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Statistical Methods, Social Network Analysis, Applied Mathematics, Simulations, Data Science, Markov Model

    Intermediate · Specialization · 3 - 6 Months

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    Coursera

    Foundations of Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting, Decision Tree Learning, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling

    4.6
    Rating, 4.6 out of 5 stars
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    10 reviews

    Intermediate · Course · 1 - 4 Weeks

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    T

    The University of Chicago

    Machine Learning: Concepts and Applications

    Skills you'll gain: Keras (Neural Network Library), Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Classification Algorithms, Supervised Learning, Regression Analysis, Random Forest Algorithm, Dimensionality Reduction, Model Evaluation, Data Preprocessing, Statistical Methods, Tensorflow, Feature Engineering, Pandas (Python Package)

    3.9
    Rating, 3.9 out of 5 stars
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    25 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Advanced Analytics, Analytics, Statistical Machine Learning, Machine Learning, Scikit Learn (Machine Learning Library), Unsupervised Learning, Machine Learning Algorithms, Workflow Management, Data Ethics, Supervised Learning, Data Preprocessing, Decision Tree Learning, Random Forest Algorithm, Verification And Validation, Python Programming, Classification Algorithms, Performance Tuning

    4.8
    Rating, 4.8 out of 5 stars
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    593 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
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    D

    DeepLearning.AI

    Linear Algebra for Machine Learning and Data Science

    Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Data Preprocessing, Machine Learning Methods, Advanced Mathematics, Data Manipulation, Applied Mathematics, Mathematical Modeling, Machine Learning, Python Programming, Algebra

    4.6
    Rating, 4.6 out of 5 stars
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    2.3K reviews

    Intermediate · Course · 1 - 4 Weeks

What brings you to Coursera today?

1234…834

In summary, here are 10 of our most popular support vector machine (svm) theory and implementation courses

  • Machine Learning Fundamentals: Dartmouth College
  • Practical Machine Learning: Foundations to Neural Networks: Dartmouth College
  • Machine Learning: Theory and Hands-on Practice with Python: University of Colorado Boulder
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Improve Accuracy with ML Ensemble Methods: Coursera
  • Data Mining: University of Illinois Urbana-Champaign
  • Applied Machine Learning in Python: University of Michigan
  • Statistical Methods for Computer Science: Johns Hopkins University
  • Foundations of Machine Learning: Coursera
  • Machine Learning: Concepts and Applications: The University of Chicago

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