Mathematics for Machine Learning

Bridging Mathematical Theory and Practical Applications

Teaching Experience at UNAM

As a professor at the Faculty of Science, National Autonomous University of Mexico (UNAM), I designed and conducted diverse courses bridging mathematical theory with practical applications. My teaching approach emphasizes understanding fundamental concepts and their real-world implementations.

Core Mathematical Courses
  • • Probability Theory
  • • Bayesian Statistics
  • • Mathematical Analysis
  • • Differential Equations
  • • Algebra
Applied Mathematics
  • • Mathematics for Biology and Physics
  • • Seminars on Actuarial Applications
  • • Stochastic Processes
  • • Risk Theory
Beginner

Foundations of Machine Learning

A comprehensive introduction to machine learning concepts, covering essential mathematical foundations and practical implementations. Perfect for beginners who want to understand the theory behind popular ML algorithms.

Course Topics:
Linear Algebra Fundamentals
Probability and Statistics
Calculus for ML
Supervised Learning
Unsupervised Learning
Model Evaluation
Python Implementation
Real-world Applications
Key Mathematical Concept:
Linear Regression: y = Xβ + ε
where β = (X'X)⁻¹X'y
Certificate of Completion Hands-on Projects
Enroll Now
Intermediate

Advanced Statistical Methods for Data Science

Deep dive into advanced statistical techniques used in modern data science. This course covers both frequentist and Bayesian approaches with practical applications in Python and R.

Course Topics:
Bayesian Inference
Hypothesis Testing
Regression Analysis
Time Series Analysis
Multivariate Statistics
Non-parametric Methods
Monte Carlo Methods
Statistical Learning Theory
Bayesian Theorem:
P(θ|D) = P(D|θ)P(θ) / P(D)
Advanced Certificate Research Projects
Enroll Now
Advanced

Mathematical Foundations of Deep Learning

Master the mathematical principles behind deep learning networks. From backpropagation to optimization theory, understand how neural networks learn from data.

Course Topics:
Neural Network Architecture
Backpropagation Algorithm
Optimization Theory
Regularization Techniques
Convolutional Networks
Recurrent Networks
Attention Mechanisms
Transfer Learning
Gradient Descent:
θ = θ - α∇J(θ)
where ∇J(θ) is the gradient of the loss function
Expert Certificate Industry Projects
Enroll Now
Advanced

Mathematics of Computer Vision

Explore the mathematical foundations of computer vision, from image processing to object detection. Learn how geometry, linear algebra, and optimization power modern CV applications.

Course Topics:
Image Processing Theory
Feature Detection
Camera Geometry
3D Reconstruction
Object Detection
Semantic Segmentation
Optical Flow
Deep Learning for Vision
Convolution Operation:
(f * g)(t) = ∫f(τ)g(t-τ)dτ
Specialized Certificate Computer Vision Projects
Enroll Now
Intermediate

Optimization Theory for Machine Learning

Coming Soon! Master optimization techniques essential for machine learning. From gradient descent to advanced optimization algorithms used in deep learning.

Course Topics:
Convex Optimization
Gradient-based Methods
Constrained Optimization
Lagrange Multipliers
Stochastic Optimization
Adam and RMSprop
Hyperparameter Tuning
Multi-objective Optimization
Lagrangian:
L(x,λ) = f(x) + λᵀg(x)
Coming Soon Advanced Optimization
Get Notified
Advanced

Stochastic Processes in Machine Learning

Dive deep into stochastic processes and their applications in machine learning. From Markov chains to random walks, understand the probabilistic foundations of modern ML algorithms.

Course Topics:
Markov Chains
Random Walks
Brownian Motion
Martingales
Gaussian Processes
Hidden Markov Models
Monte Carlo Methods
Reinforcement Learning
Markov Property:
P(Xₙ₊₁|X₀,...,Xₙ) = P(Xₙ₊₁|Xₙ)
Advanced Certificate Research Applications
Enroll Now

Ready to Master Machine Learning Mathematics?

Join thousands of students who have transformed their understanding of machine learning through solid mathematical foundations. With over 5 years of teaching experience at UNAM and practical industry expertise, I provide the perfect blend of theory and application.

Contact Me Today