One of the most useful areas in machine learning is discovering hidden patterns from unlabeled data. Add the fundamentals of this in-demand skill to your Data Science toolkit. In this course, we will learn selected unsupervised learning methods for dimensionality reduction, clustering, and learning latent features. We will also focus on real-world applications such as recommender systems with hands-on examples of product recommendation algorithms.
Este curso forma parte de Programa especializado: Machine Learning: Theory and Hands-on Practice with Python
Ofrecido Por


Acerca de este Curso
Calculus, Linear algebra, Python, NumPy, Pandas, Matplotlib, and Scikit-learn.
Qué aprenderás
Explain what unsupervised learning is, and list methods used in unsupervised learning.
List and explain algorithms for various matrix factorization methods, and what each is used for.
List and explain algorithms for various matrix factorization methods, and what each is used for.
Habilidades que obtendrás
- Dimensionality Reduction
- Unsupervised Learning
- Cluster Analysis
- Recommender Systems
- Matrix Factorization
Calculus, Linear algebra, Python, NumPy, Pandas, Matplotlib, and Scikit-learn.
Ofrecido por
Comienza a trabajar para obtener tu título
Programa - Qué aprenderás en este curso
Unsupervised Learning Intro
Clustering
Recommender System
Matrix Factorization
Acerca de Programa especializado: Machine Learning: Theory and Hands-on Practice with Python

Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
¿Qué recibiré si me suscribo a este Programa especializado?
¿Hay ayuda económica disponible?
¿Tienes más preguntas? Visita el Centro de Ayuda al Estudiante.