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
Skills you'll gain: Data Analysis, Machine Learning Algorithms, Statistical Analysis, Probability & Statistics, Probability Distribution, R Programming, Machine Learning Methods, Statistical Methods, R (Software), Applied Machine Learning, Statistical Machine Learning, Statistics, Statistical Modeling, Machine Learning, Statistical Inference, Classification Algorithms, Statistical Programming, Correlation Analysis, Data Manipulation, Supervised Learning
Skills you'll gain: Responsible AI, Microsoft Azure, Unsupervised Learning, Databricks, MLOps (Machine Learning Operations), Applied Machine Learning, Classification Algorithms, Model Training, Regression Analysis, Scikit Learn (Machine Learning Library), Predictive Modeling, Model Deployment, Cloud Management, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Supervised Learning, Machine Learning Algorithms, Data Pipelines, Data Transformation
University of Washington
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
Skills you'll gain: Model Evaluation, Unsupervised Learning, Model Training, Machine Learning Methods, Dimensionality Reduction, Data Preprocessing, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Model Optimization, Recurrent Neural Networks (RNNs), Classification 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
Alberta Machine Intelligence Institute
Skills you'll gain: Supervised Learning, Model Optimization, Machine Learning Algorithms, Machine Learning Methods, Applied Machine Learning, Classification Algorithms, Model Evaluation, Jupyter, Statistical Machine Learning, Decision Tree Learning, Model Training, Machine Learning, Data Preprocessing, Business Solutions, Python Programming, Regression Analysis, Performance Analysis, Data Processing
Skills you'll gain: PySpark, Model Optimization, Model Training, Applied Machine Learning, Data Manipulation, Machine Learning, Data Preprocessing, Logistic Regression
DeepLearning.AI
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
National Taiwan University
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
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
Skills you'll gain: Model Evaluation, Supervised Learning, Machine Learning Methods, AI Personalization, Classification Algorithms, Machine Learning, Model Training, Logistic Regression, Model Optimization, Data Analysis, Driving engagement, Persona (User Experience)
Board Infinity
Skills you'll gain: Classification Algorithms, Java Programming, Data Preprocessing, Machine Learning Software, Model Training, Model Deployment, Model Evaluation, Decision Tree Learning, Logistic Regression
In summary, here are 10 of our most popular math for machine learning courses
- Machine Learning with R: Build, Analyze & Predict: EDUCBA
- Microsoft Azure Machine Learning for Data Scientists: Microsoft
- Machine Learning Foundations: A Case Study Approach: University of Washington
- Machine Learning Foundations: Packt
- Machine Learning in Python: Analyze & Apply: EDUCBA
- Machine Learning Algorithms: Supervised Learning Tip to Tail: Alberta Machine Intelligence Institute
- Machine Learning with PySpark: Edureka
- Advanced Learning Algorithms: DeepLearning.AI
- 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
- Create Machine Learning Models in Microsoft Azure: Microsoft
