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  • Kernel Method

Results for "kernel method"


  • Status: Preview
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    D

    DeepLearning.AI

    심층 신경망 개선: 하이퍼파라미터 튜닝, 정규화 및 최적화

    Skills you'll gain: Tensorflow, Deep Learning, Performance Tuning, Model Evaluation, Machine Learning Methods, Artificial Neural Networks, Debugging, Machine Learning, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    7 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California, Irvine

    Cluster Analysis, Association Mining, and Model Evaluation

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Analysis, Regression Analysis, Statistical Analysis, Data Mining, Predictive Analytics, Anomaly Detection, Fraud detection, Machine Learning, Correlation Analysis, Probability & Statistics, Scatter Plots, Market Analysis, Classification Algorithms, Collaborative Software

    4.5
    Rating, 4.5 out of 5 stars
    ·
    47 reviews

    Intermediate · Course · 1 - 4 Weeks

  • 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

  • Status: Free Trial
    Free Trial
    D

    Dartmouth College

    C Programming: Using Linux Tools and Libraries - 7

    Skills you'll gain: File I/O, Embedded Software, C (Programming Language), Linux, Embedded Systems, Build Tools, Command-Line Interface, Operating Systems, Program Development, Software Installation, Development Environment, Application Development, Computer Programming

    4.7
    Rating, 4.7 out of 5 stars
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    31 reviews

    Beginner · Course · 1 - 3 Months

  • C

    Coursera

    Principal Component Analysis with NumPy

    Skills you'll gain: Exploratory Data Analysis, NumPy, Data Visualization, Data Analysis, Seaborn, Matplotlib, Statistical Visualization, Jupyter, Dimensionality Reduction, Data Science, Machine Learning Methods, Python Programming, Data Preprocessing

    4.6
    Rating, 4.6 out of 5 stars
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    298 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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

    EDUCBA

    Ethical Hacking with Kali Linux: Analyze & Apply

    Skills you'll gain: Penetration Testing, Exploitation techniques, Brute-force attacks, Cyber Security Assessment, Vulnerability Assessments, Authentications, Wireless Networks, Network Security, Linux, Encryption, Microsoft Windows, Cryptography, Operating Systems

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    É

    École Polytechnique Fédérale de Lausanne

    Big Data Analysis with Scala and Spark

    Skills you'll gain: Apache Spark, Scala Programming, Distributed Computing, Big Data, Data Manipulation, Data Processing, Performance Tuning, Data Persistence, SQL, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.6K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Applied Machine Learning: Techniques and Applications

    Skills you'll gain: Computer Vision, Model Evaluation, Supervised Learning, Image Analysis, Data Preprocessing, Applied Machine Learning, Feature Engineering, Machine Learning Algorithms, Predictive Modeling, Machine Learning, Data Cleansing, Scikit Learn (Machine Learning Library), Data Integration, Data Transformation, Classification Algorithms

    3.7
    Rating, 3.7 out of 5 stars
    ·
    12 reviews

    Intermediate · Course · 1 - 4 Weeks

  • 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
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    18 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    Customer Segmentation with K-Means: Model & Visualize

    Skills you'll gain: Customer Analysis, Statistical Visualization, Unsupervised Learning, Customer Insights, Correlation Analysis, Data Preprocessing, Pandas (Python Package), Heat Maps, Data Manipulation, Seaborn, Histogram, Scatter Plots, Matplotlib, Exploratory Data Analysis, Applied Machine Learning, Data Visualization Software

    Mixed · Course · 1 - 4 Weeks

  • C

    Coursera

    Data Analysis Using Pyspark

    Skills you'll gain: PySpark, Matplotlib, Apache Spark, Big Data, Data Processing, Distributed Computing, Data Management, Data Visualization, Data Analysis, Data Manipulation, Data Cleansing, Query Languages, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    315 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    Python: Implement & Evaluate Random Forests for ML

    Skills you'll gain: Model Evaluation, Supervised Learning, Data Preprocessing, Random Forest Algorithm, Applied Machine Learning, Decision Tree Learning, Feature Engineering, Machine Learning Algorithms, Classification Algorithms, Predictive Modeling, Data Analysis, Python Programming

    Mixed · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular kernel method courses

  • 심층 신경망 개선: 하이퍼파라미터 튜닝, 정규화 및 최적화: DeepLearning.AI
  • Cluster Analysis, Association Mining, and Model Evaluation: University of California, Irvine
  • Scikit-Learn to Solve Regression Machine Learning Problems: Coursera
  • C Programming: Using Linux Tools and Libraries - 7: Dartmouth College
  • Principal Component Analysis with NumPy: Coursera
  • Ethical Hacking with Kali Linux: Analyze & Apply: EDUCBA
  • Big Data Analysis with Scala and Spark: École Polytechnique Fédérale de Lausanne
  • Applied Machine Learning: Techniques and Applications: Johns Hopkins University
  • Scikit-Learn For Machine Learning Classification Problems: Coursera
  • Customer Segmentation with K-Means: Model & Visualize: EDUCBA

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