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  • Mathematics For Machine Learning

Mathematics for Machine Learning Courses

Mathematics for machine learning courses can help you learn linear algebra, calculus, probability, and statistics. You can build skills in optimization techniques, data analysis, and algorithm development. Many courses introduce tools like Python libraries such as NumPy and SciPy, that support implementing mathematical concepts in AI applications. You'll also explore key topics like regression analysis, dimensionality reduction, and neural networks, all of which are crucial for developing effective machine learning models.


Popular Mathematics for Machine Learning Courses and Certifications


  • P

    Packt

    Foundations of Data Science and Machine Learning with Python

    Skills you'll gain: Pandas (Python Package), Matplotlib, NumPy, Statistical Visualization, Machine Learning Algorithms, Applied Machine Learning, Data Manipulation, Pivot Tables And Charts, Model Optimization, Machine Learning Methods, Linear Algebra, Natural Language Processing, Deep Learning, Programming Principles, Machine Learning, Python Programming, Data Science, Numerical Analysis, Computer Programming, Artificial Neural Networks

    5
    Rating, 5 out of 5 stars
    ·
    6 reviews

    Intermediate · Course · 1 - 3 Months

  • P

    Packt

    Foundations of ML & Python for Data Science

    Skills you'll gain: Model Evaluation, Statistical Methods, Data Manipulation, Python Programming, Applied Machine Learning, Pandas (Python Package), Data Science, Statistical Analysis, NumPy, Machine Learning Methods, Machine Learning, Statistical Inference, Probability Distribution, Probability

    Beginner · Course · 1 - 4 Weeks

  • P

    Packt

    Matrix Calculus for Data Science & Machine Learning

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

    Intermediate · Course · 1 - 3 Months

  • S

    Stanford University

    Fundamentals of Machine Learning for Healthcare

    Skills you'll gain: Machine Learning Methods, Healthcare Ethics, Data Ethics, Statistical Machine Learning, Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Responsible AI, Artificial Neural Networks, Healthcare Industry Knowledge, Model Evaluation, Medical Science and Research, Model Training, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Supervised Learning, Health Informatics, Generative Model Architectures, Deep Learning, Health Policy

    4.8
    Rating, 4.8 out of 5 stars
    ·
    628 reviews

    Beginner · Course · 1 - 3 Months

  • N

    New York University

    Guided Tour of Machine Learning in Finance

    Skills you'll gain: Supervised Learning, Machine Learning Methods, Model Evaluation, Applied Machine Learning, Statistical Machine Learning, Machine Learning, Statistical Methods, Artificial Neural Networks, Statistical Modeling, Predictive Modeling, Model Training, Scikit Learn (Machine Learning Library), Regression Analysis, Deep Learning, Tensorflow, Logistic Regression, Jupyter, Reinforcement Learning

    3.8
    Rating, 3.8 out of 5 stars
    ·
    681 reviews

    Intermediate · Course · 1 - 4 Weeks

  • P

    Packt

    Applied Machine Learning and Model Optimization

    Skills you'll gain: Supervised Learning, Model Optimization, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Predictive Modeling, Model Training, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Data Transformation, Fine-tuning

    Advanced · Course · 1 - 3 Months

  • P

    Packt

    Foundations of Machine Learning with Azure

    Skills you'll gain: Data Preprocessing, Model Deployment, Feature Engineering, Machine Learning Methods, Microsoft Azure, Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Data Processing, Cloud Deployment, Machine Learning Software, Data Cleansing, Supervised Learning, Data Transformation, Model Training, Artificial Intelligence and Machine Learning (AI/ML), Model Optimization, Data Quality

    Intermediate · Course · 1 - 4 Weeks

  • U

    University of Washington

    Machine Learning Foundations: A Case Study Approach

    Skills you'll gain: Model Evaluation, Applied Machine Learning, Feature Engineering, Machine Learning Methods, Regression Analysis, Machine Learning, Image Analysis, Machine Learning Algorithms, AI Personalization, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Model Training, Artificial Intelligence, Deep Learning, Computer Vision, Transfer Learning, Application Development, Predictive Modeling, Model Deployment, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    14K reviews

    Mixed · Course · 1 - 3 Months

  • A

    Alberta Machine Intelligence Institute

    Data for Machine Learning

    Skills you'll gain: Feature Engineering, Data Preprocessing, Model Evaluation, Data Quality, Model Training, Data Validation, Data Cleansing, Data Transformation, Verification And Validation, Applied Machine Learning, Machine Learning, Responsible AI, Machine Learning Algorithms, Algorithms, Python Programming, Computer Programming, Linear Algebra, Statistical Analysis

    4.4
    Rating, 4.4 out of 5 stars
    ·
    98 reviews

    Intermediate · Course · 1 - 4 Weeks

  • N

    National Taiwan University

    機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

    Skills you'll gain: Classification Algorithms, Supervised Learning, Machine Learning Methods, Model Training, Machine Learning, Machine Learning Algorithms, Logistic Regression, Data Validation, Statistical Machine Learning, Applied Machine Learning, Model Evaluation, Algorithms, Regression Analysis, Model Optimization, Verification And Validation, Feature Engineering, Data Transformation

    4.9
    Rating, 4.9 out of 5 stars
    ·
    331 reviews

    Intermediate · Course · 1 - 3 Months

  • P

    Packt

    Foundations of Data Science and Machine Learning with Python

    Skills you'll gain: Predictive Modeling, Matplotlib, Machine Learning Methods, Applied Machine Learning, Seaborn, Statistical Modeling, Data Visualization, Plot (Graphics), Regression Analysis, Machine Learning Algorithms, Pandas (Python Package), Predictive Analytics, Statistical Analysis, Scientific Visualization, Machine Learning Software, Machine Learning, Supervised Learning, Data Science, Statistical Methods, Probability & Statistics

    Intermediate · Course · 1 - 3 Months

  • A

    Alberta Machine Intelligence Institute

    Introduction to Applied Machine Learning

    Skills you'll gain: Data Preprocessing, Data Ethics, Applied Machine Learning, Machine Learning Methods, Machine Learning, Machine Learning Algorithms, Product Lifecycle Management, Case Studies, Data Collection, Data Capture, Supervised Learning, Business Requirements, Data Quality, Business Analysis, Unsupervised Learning, Artificial Intelligence

    4.7
    Rating, 4.7 out of 5 stars
    ·
    747 reviews

    Intermediate · Course · 1 - 4 Weeks

1…8910…834

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

  • Foundations of Data Science and Machine Learning with Python: Packt
  • Foundations of ML & Python for Data Science: Packt
  • Matrix Calculus for Data Science & Machine Learning: Packt
  • Fundamentals of Machine Learning for Healthcare: Stanford University
  • Guided Tour of Machine Learning in Finance: New York University
  • Applied Machine Learning and Model Optimization: Packt
  • Foundations of Machine Learning with Azure: Packt
  • Machine Learning Foundations: A Case Study Approach: University of Washington
  • Data for Machine Learning: Alberta Machine Intelligence Institute
  • 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations: National Taiwan University

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