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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


  • N

    National Taiwan University

    機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

    Skills you'll gain: Supervised Learning, Model Training, Machine Learning, Machine Learning Methods, Statistical Machine Learning, Model Evaluation, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Theoretical Computer Science, Classification Algorithms, Mathematical Modeling, Statistical Methods, Mathematical Theory & Analysis, Probability, Probability & Statistics, Algorithms

    ★ 4.9 (937) · Beginner · Course · 1 - 3 Months

  • S

    SkillUp

    Machine Learning for Medical Data

    Skills you'll gain: Machine Learning Methods, Healthcare Ethics, Health Informatics, Machine Learning, Deep Learning, Statistical Machine Learning, Model Training, Convolutional Neural Networks, Data Preprocessing, Predictive Modeling, Electronic Medical Record System, AI Personalization, Machine Learning Algorithms, Recurrent Neural Networks (RNNs), Model Evaluation, Decision Intelligence, Data Analysis

    Intermediate · Course · 1 - 4 Weeks

  • M

    Microsoft

    Create Machine Learning Models in Microsoft Azure

    Skills you'll gain: Unsupervised Learning, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Convolutional Neural Networks, Exploratory Data Analysis, Deep Learning, Microsoft Azure, Data Visualization, Classification Algorithms, Applied Machine Learning, Regression Analysis, Predictive Modeling, Data Analysis, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Data Science, Model Training, Transfer Learning, Databricks, Machine Learning

    ★ 4.5 (331) · Intermediate · Course · 1 - 4 Weeks

  • D

    DeepLearning.AI

    Advanced Learning Algorithms

    Skills you'll gain: Model Training, Machine Learning Algorithms, Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Responsible AI, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Model Optimization, Artificial Neural Networks, Logistic Regression, Regression Analysis

    ★ 4.9 (8.7K) · Beginner · Course · 1 - 4 Weeks

  • T

    The University of Chicago

    Machine Learning: Concepts and Applications

    Skills you'll gain: Keras (Neural Network Library), Machine Learning Methods, Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Statistical Machine Learning, Machine Learning Software, Decision Tree Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Classification Algorithms, Supervised Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML), Random Forest Algorithm, Model Training, Dimensionality Reduction, Model Evaluation, Data Preprocessing

    ★ 3.9 (25) · 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 (747) · Intermediate · Course · 1 - 4 Weeks

  • 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

    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

  • S

    Sungkyunkwan University

    Machine Learning Basics

    Skills you'll gain: Machine Learning Algorithms, Machine Learning Methods, Machine Learning, Python Programming, Supervised Learning, Model Evaluation, Scikit Learn (Machine Learning Library), Logistic Regression, Analysis, Applied Machine Learning, Regression Analysis, Model Training, Unsupervised Learning, Mathematics and Mathematical Modeling, Statistical Methods, Linear Algebra

    ★ 4.4 (93) · Mixed · Course · 1 - 4 Weeks

  • P

    Packt

    Fundamentals of Machine Learning

    Skills you'll gain: LLM Application, Machine Learning Methods, Applied Machine Learning, Machine Learning Algorithms, Fine-tuning, Model Training

    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

  • A

    Arizona State University

    Introduction to Machine Learning with Python

    Skills you'll gain: Supervised Learning, Unsupervised Learning, Generative Adversarial Networks (GANs), Generative AI, Model Training, Deep Learning, Image Analysis, Machine Learning Methods, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Machine Learning, Generative Model Architectures, Artificial Neural Networks, Model Evaluation, Data Processing, Classification Algorithms, Computer Vision, Computer Programming, Regression Analysis

    ★ 3.6 (25) · Beginner · Course · 1 - 4 Weeks

1…678…834

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

  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
  • Machine Learning for Medical Data : SkillUp
  • Create Machine Learning Models in Microsoft Azure: Microsoft
  • Advanced Learning Algorithms: DeepLearning.AI
  • Machine Learning: Concepts and Applications: The University of Chicago
  • Introduction to Applied Machine Learning: Alberta Machine Intelligence Institute
  • Foundations of ML & Python for Data Science: Packt
  • Applied Machine Learning and Model Optimization: Packt
  • Machine Learning Basics: Sungkyunkwan University
  • Fundamentals of Machine Learning: Packt

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