Math For Machine Learning Courses
Courses in Math for Machine Learning can help you learn linear algebra, calculus, probability, and statistics. You can build skills in data analysis, model evaluation, and algorithm optimization. Many courses introduce tools like Python libraries such as NumPy and SciPy, that support implementing mathematical concepts in AI and artificial intelligence projects. You'll also explore techniques like gradient descent and matrix factorization, which are crucial for developing effective machine learning models.
Popular Math For Machine Learning Courses and Certifications
National Taiwan University
Skills you'll gain: Machine Learning Algorithms, Model Evaluation, Classification Algorithms, Machine Learning Methods, Model Training, Algorithms, Supervised Learning, Logistic Regression, Machine Learning, Applied Machine Learning, Regression Analysis, Feature Engineering, Statistical Methods, Model Optimization, Verification And Validation, Data Transformation
Fractal Analytics
Skills you'll gain: Feature Engineering, Model Evaluation, Machine Learning Algorithms, Model Optimization, Machine Learning Methods, Random Forest Algorithm, Advanced Analytics, Algorithms, Statistical Machine Learning, Applied Machine Learning, Decision Tree Learning, Predictive Modeling, Data Preprocessing, Fine-tuning, Classification And Regression Tree (CART)
University of Minnesota
Skills you'll gain: Dimensionality Reduction, Linear Algebra, Unsupervised Learning, Machine Learning Methods, Numerical Analysis, Mathematical Modeling, Applied Mathematics, Applied Machine Learning, Data Manipulation, Algorithms, Python Programming
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
New York University
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
Skills you'll gain: Data Preprocessing, Tensorflow, Scikit Learn (Machine Learning Library), Machine Learning, Applied Machine Learning, Feature Engineering, Deep Learning, Machine Learning Algorithms, Matplotlib, Jupyter, Python Programming, Data Wrangling, Data Processing, NumPy, Data Cleansing, Model Training, Data Manipulation, Data Transformation, Artificial Neural Networks, Seaborn
Johns Hopkins University
Skills you'll gain: Computer Vision, Model Evaluation, Supervised Learning, Image Analysis, Data Preprocessing, Applied Machine Learning, Machine Learning Methods, Feature Engineering, Machine Learning Algorithms, Data Processing, Model Training, Model Optimization, Machine Learning, Data Cleansing, Scikit Learn (Machine Learning Library), Machine Learning Software, Data Integration, Data Transformation, Classification Algorithms, Regression Analysis
University of Glasgow
Skills you'll gain: Model Training, Model Evaluation, Data Preprocessing, Machine Learning Methods, Statistical Methods, Machine Learning Software, Statistical Machine Learning, Data Validation, Data Processing, Data Quality, Mathematical Software, Classification Algorithms, Machine Learning Algorithms
Skills you'll gain: Matplotlib, Plot (Graphics), 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, Model Optimization, Machine Learning Algorithms, Text Mining, Data Manipulation, Predictive Modeling, Model Training, Unsupervised Learning, Data Management
The University of Chicago
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
Skills you'll gain: Exploratory Data Analysis, Logistic Regression, Correlation Analysis, Applied Machine Learning, Model Evaluation, Data Modeling
Skills you'll gain: Supervised Learning, Model Optimization, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Algorithms, Predictive Modeling, Model Training, Data Preprocessing, Classification Algorithms, Dimensionality Reduction, Data Transformation, Fine-tuning
In summary, here are 10 of our most popular math for machine learning courses
- 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations: National Taiwan University
- Advanced Machine Learning Algorithms: Fractal Analytics
- Matrix Methods: University of Minnesota
- Foundations of Data Science and Machine Learning with Python: Packt
- Guided Tour of Machine Learning in Finance: New York University
- Master Machine Learning with TensorFlow: Basics to Advanced: EDUCBA
- Applied Machine Learning: Techniques and Applications: Johns Hopkins University
- Machine Learning and its Applications: University of Glasgow
- Machine Learning in Python: Analyze & Apply: EDUCBA
- Machine Learning: Concepts and Applications: The University of Chicago
