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Math For Machine Learning Courses

Courses in Math for Machine Learning often teach linear algebra, calculus, probability, and statistics, providing a solid foundation for understanding algorithms. You can build skills in optimization techniques, data analysis, and model evaluation, which are crucial for effective machine learning applications. Many courses introduce tools like Python libraries such as NumPy and TensorFlow, which help you implement mathematical concepts in AI projects and enhance your ability to work with data-driven models.


Popular Math For Machine Learning Courses and Certifications


  • Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of Data Science and Machine Learning with Python

    Skills you'll gain: Matplotlib, NumPy, Data Visualization, Data Manipulation, Linear Algebra, Seaborn, Natural Language Processing, Deep Learning, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Data Preprocessing, Data Science, Regression Analysis, Data Structures, Logistic Regression

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    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
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    12 reviews

    Beginner · Course · 1 - 3 Months

  • 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
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    8 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
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    IBM

    Supervised Machine Learning: Regression

    Skills you'll gain: Supervised Learning, Regression Analysis, Applied Machine Learning, Predictive Modeling, Machine Learning, Machine Learning Algorithms, Statistical Modeling, Logistic Regression, Scikit Learn (Machine Learning Library), Model Evaluation, Data Preprocessing, Feature Engineering, Statistical Analysis, Classification Algorithms

    4.7
    Rating, 4.7 out of 5 stars
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    818 reviews

    Intermediate · Course · 1 - 3 Months

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    Northeastern University

    Statistical Learning for Engineering Part 2

    Skills you'll gain: PyTorch (Machine Learning Library), Unsupervised Learning, Reinforcement Learning, Supervised Learning, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Convolutional Neural Networks, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Transfer Learning, Decision Tree Learning, Classification Algorithms, Random Forest Algorithm, Autoencoders, Predictive Modeling, Feature Engineering

    Intermediate · Course · 1 - 3 Months

  • P

    Packt

    Matrix Calculus for Data Science & Machine Learning

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

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    Packt

    Machine Learning with PyTorch and Scikit-Learn

    Skills you'll gain: Reinforcement Learning, Dimensionality Reduction, PyTorch (Machine Learning Library), Machine Learning Algorithms, Data Preprocessing, Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Machine Learning Methods, Deep Learning, Transfer Learning, Applied Machine Learning, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Machine Learning, Artificial Neural Networks, Data Processing, Natural Language Processing, Feature Engineering

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
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    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
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    12 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    EDUCBA

    Machine Learning in Python: Analyze & Apply

    Skills you'll gain: Matplotlib, NumPy, Pandas (Python Package), Applied Machine Learning, Python Programming, Scikit Learn (Machine Learning Library), Data Visualization, Supervised Learning, Feature Engineering, Machine Learning, Natural Language Processing, Machine Learning Algorithms, Text Mining, Data Manipulation, Unsupervised Learning, Model Evaluation, Data Preprocessing, Classification Algorithms

    Mixed · Course · 1 - 4 Weeks

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    EDUCBA

    Machine Learning with Python & Statistics

    Skills you'll gain: Sampling (Statistics), Data Mining, Statistical Hypothesis Testing, Probability, Linear Algebra, Statistical Analysis, Statistical Inference, Data Analysis, Probability Distribution, Statistics, Machine Learning Algorithms, Machine Learning, Python Programming

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Alberta Machine Intelligence Institute

    Optimizing Machine Learning Performance

    Skills you'll gain: Responsible AI, Data Ethics, MLOps (Machine Learning Operations), Model Deployment, Business Operations, Machine Learning, Ethical Standards And Conduct, Operational Analysis, Applied Machine Learning, Business Strategy, AI Enablement, Model Evaluation, Data Maintenance, Risk Mitigation, Performance Metric, Continuous Monitoring, Systems Integration, Stakeholder Communications

    4.4
    Rating, 4.4 out of 5 stars
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    51 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: New
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    EDUCBA

    Machine Learning with R: Build, Analyze & Predict

    Skills you'll gain: Data Analysis, Statistical Analysis, Probability Distribution, R Programming, Exploratory Data Analysis, Statistical Modeling, Machine Learning, Statistical Inference, Classification Algorithms, Data Manipulation, Supervised Learning, Random Forest Algorithm, Regression Analysis, Model Evaluation, Decision Tree Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    12 reviews

    Mixed · Course · 1 - 4 Weeks

Searches related to math for machine learning

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In summary, here are 10 of our most popular math for machine learning courses

  • Foundations of Data Science and Machine Learning with Python: Packt
  • Advanced Machine Learning Algorithms: Fractal Analytics
  • Scikit-Learn to Solve Regression Machine Learning Problems: Coursera
  • Supervised Machine Learning: Regression: IBM
  • Statistical Learning for Engineering Part 2: Northeastern University
  • Matrix Calculus for Data Science & Machine Learning: Packt
  • Machine Learning with PyTorch and Scikit-Learn: Packt
  • Applied Machine Learning: Techniques and Applications: Johns Hopkins University
  • Machine Learning in Python: Analyze & Apply: EDUCBA
  • Machine Learning with Python & Statistics: EDUCBA

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