Serrano.Academy Courses

Logistic Regression and the Perceptron Algorithm - A Friendly Introduction

Friendly introduction to logistic regression and perceptron algorithm, covering key concepts like data classification, gradient descent, and neural networks with minimal math and visual explanations.

• YouTube
• 45 minutes
• On-Demand
• Free Video

Linear Regression - A Friendly Introduction

Discover the fundamentals of linear regression through visual explanations, exploring concepts like slope, y-intercept, and error measurement to predict housing prices effectively.

• YouTube
• 31 minutes
• On-Demand
• Free Video

How Does Netflix Recommend Movies? Matrix Factorization

Explore matrix factorization in recommender systems, focusing on Netflix's movie recommendation algorithm. Learn about dependencies, error functions, and predicting user ratings.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Shannon Entropy and Information Gain

Explore Shannon entropy and information gain concepts through interactive examples, quizzes, and games. Learn to calculate probabilities and apply formulas for various scenarios.

• YouTube
• 21 minutes
• On-Demand
• Free Video

A Friendly Introduction to Convolutional Neural Networks and Image Recognition

Friendly explanation of image recognition using Convolutional Neural Networks, covering basics to advanced concepts. Suitable for beginners, with minimal math required.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Machine Learning - Testing and Error Metrics

Explore machine learning model evaluation, including metrics, error types, cross-validation, and optimization techniques for improved performance and decision-making.

• YouTube
• 45 minutes
• On-Demand
• Free Video

A Friendly Introduction to Deep Learning and Neural Networks

Explore neural networks and deep learning concepts, from gradient descent to activation functions, in this friendly introduction to AI fundamentals.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Machine learning en espanol

Introducción práctica al aprendizaje automático en español, cubriendo técnicas supervisadas y no supervisadas con aplicaciones reales como reconocimiento de imágenes y sistemas de recomendación.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

Natural Language Processing

Explore Latent Dirichlet Allocation through a two-part series, covering its fundamentals and training using Gibbs Sampling.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Probability

Explore Bayes Theorem, Hidden Markov Models, Shannon Entropy, Naive Bayes classifier, Beta distribution, and Thompson sampling in this friendly introduction to key probability concepts.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

Generative Models

Explore denoising autoencoders, VAEs, GANs, and RBMs in this comprehensive introduction to generative models, covering key concepts and applications in machine learning.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

Unsupervised Learning

Explore key unsupervised learning techniques including clustering, dimensionality reduction, and generative models. Gain insights into real-world applications like recommendation systems and image compression.

• YouTube
• 4 hours 30 minutes
• On-Demand
• Free Video

Neural Networks

This Course is a friendly introduction series to machine learning, deep learning, neural networks and generative adversarial networks.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

General Machine Learning

Explore key machine learning concepts, algorithms, and evaluation methods in this comprehensive introduction to the field.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

Machine Learning

Comprehensive introduction to key machine learning concepts, algorithms, and applications, covering testing, error metrics, recommendation systems, and various classification methods.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video