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  • Polynomial Svm For Classification Tasks

Results for "polynomial svm for classification tasks"


  • Status: Free Trial
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    Stanford University

    Probabilistic Graphical Models 2: Inference

    Skills you'll gain: Bayesian Network, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Machine Learning Algorithms, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
    ·
    488 reviews

    Advanced · Course · 1 - 3 Months

  • P

    Packt

    Machine Learning: Random Forest with Python from Scratch©

    Skills you'll gain: Matplotlib, Applied Machine Learning, Random Forest Algorithm, Predictive Modeling, Predictive Analytics, Machine Learning Algorithms, Data Visualization, Machine Learning, Programming Principles, Data Manipulation, Feature Engineering, Data Cleansing, Supervised Learning, Python Programming, Data Science, Data Processing, NumPy, Pandas (Python Package)

    Beginner · Course · 1 - 3 Months

  • C

    Coursera

    Basic Image Classification with TensorFlow

    Skills you'll gain: Keras (Neural Network Library), Tensorflow, Image Analysis, Artificial Neural Networks, Deep Learning, Machine Learning Methods, Computer Vision, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    847 reviews

    Beginner · Guided Project · Less Than 2 Hours

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    New York University

    Fundamentals of Machine Learning in Finance

    Skills you'll gain: Supervised Learning, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Decision Tree Learning, Machine Learning, Financial Trading, Financial Market, Reinforcement Learning, Scikit Learn (Machine Learning Library), Financial Services, Regression Analysis, Correlation Analysis, Exploratory Data Analysis, Portfolio Management, Python Programming, Artificial Neural Networks, Jupyter

    3.7
    Rating, 3.7 out of 5 stars
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    341 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    S

    SAS

    Four Rare Machine Learning Skills All Data Scientists Need

    Skills you'll gain: Predictive Modeling, Predictive Analytics, Marketing Analytics, Statistical Machine Learning, Machine Learning, Data Science, Supervised Learning, Applied Machine Learning, Marketing, Statistical Analysis

    4.7
    Rating, 4.7 out of 5 stars
    ·
    9 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Imperial College London

    Mathematics for Machine Learning: PCA

    Skills you'll gain: Dimensionality Reduction, NumPy, Probability & Statistics, Jupyter, Data Science, Statistics, Linear Algebra, Python Programming, Machine Learning, Calculus

    4
    Rating, 4 out of 5 stars
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    3.2K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    T

    The University of Chicago

    Machine Learning: Concepts and Applications

    Skills you'll gain: Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Classification And Regression Tree (CART), Decision Tree Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Supervised Learning, Regression Analysis, Random Forest Algorithm, Dimensionality Reduction, Statistical Methods, Tensorflow, Feature Engineering, Artificial Neural Networks, Pandas (Python Package)

    3.8
    Rating, 3.8 out of 5 stars
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    24 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    U

    University of Illinois Urbana-Champaign

    Machine Learning for Accounting with Python

    Skills you'll gain: Machine Learning Algorithms, Unsupervised Learning, Scikit Learn (Machine Learning Library), Machine Learning, Text Mining, Applied Machine Learning, Time Series Analysis and Forecasting, Data Processing, Supervised Learning, Predictive Modeling, Python Programming, Regression Analysis, Feature Engineering, Jupyter, Pandas (Python Package), Natural Language Processing, Statistical Analysis, Performance Metric

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    43 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    E

    Edureka

    Machine Learning with PySpark

    Skills you'll gain: PySpark, Performance Tuning, Machine Learning

    Intermediate · Course · 1 - 4 Weeks

  • P

    Packt

    Matrix Calculus for Data Science & Machine Learning

    Skills you'll gain: Calculus, Applied Mathematics, NumPy, Tensorflow, Machine Learning, Python Programming, Derivatives, Algorithms, Development Environment

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Data Analysis with Python Project

    Skills you'll gain: Dimensionality Reduction, Data Analysis, Supervised Learning, Anomaly Detection, Machine Learning, Machine Learning Algorithms, Statistical Analysis, Unsupervised Learning, Data Mining, Analytics, Predictive Modeling, Regression Analysis, Scikit Learn (Machine Learning Library), Classification And Regression Tree (CART), Exploratory Data Analysis, Project Planning

    5
    Rating, 5 out of 5 stars
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    7 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning: Regression

    Skills you'll gain: Regression Analysis, Predictive Modeling, Supervised Learning, Statistical Modeling, Applied Machine Learning, Predictive Analytics, Feature Engineering, Machine Learning, Statistical Methods, Python Programming, Data Manipulation, Algorithms, Performance Testing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    5.6K reviews

    Mixed · Course · 1 - 3 Months

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In summary, here are 10 of our most popular polynomial svm for classification tasks courses

  • Probabilistic Graphical Models 2: Inference: Stanford University
  • Machine Learning: Random Forest with Python from Scratch©: Packt
  • Basic Image Classification with TensorFlow: Coursera
  • Fundamentals of Machine Learning in Finance: New York University
  • Four Rare Machine Learning Skills All Data Scientists Need: SAS
  • Mathematics for Machine Learning: PCA: Imperial College London
  • Machine Learning: Concepts and Applications: The University of Chicago
  • Machine Learning for Accounting with Python: University of Illinois Urbana-Champaign
  • Machine Learning with PySpark: Edureka
  • Matrix Calculus for Data Science & Machine Learning: Packt

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