One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.
Acerca de este Curso
Habilidades que obtendrás
- 5 stars66,45 %
- 4 stars22,35 %
- 3 stars6,90 %
- 2 stars2,51 %
- 1 star1,77 %
Principales reseñas sobre APRENDIZAJE AUTOMÁTICO PRÁCTICO
Some of the terms used here vary from the terms used in the industry. For example recall, precision etc. Overall this is a very good course with provides basics of machine learning.
Awesome course. Would recommend it, but only to those who have a bit of stats and R background. This definitely helped me get a solid enough understanding of using R for machine learning.
excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!
Excellent introduction to basic ML techniques. A lot of material covered in a short period of time! I will definitely seek more advanced training out of the inspiration provided by this class.
¿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.