Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.
Ce cours fait partie de la Spécialisation Big Data
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À propos de ce cours
Compétences que vous acquerrez
- Machine Learning Concepts
- Knime
- Machine Learning
- Apache Spark
Offert par

Université de Californie à San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Programme de cours : ce que vous apprendrez dans ce cours
Welcome
Introduction to Machine Learning with Big Data
Data Exploration
Data Preparation
Classification
Evaluation of Machine Learning Models
Avis
- 5 stars70,25 %
- 4 stars23,83 %
- 3 stars4,12 %
- 2 stars1,04 %
- 1 star0,75 %
Meilleurs avis pour MACHINE LEARNING WITH BIG DATA
Good content and delivery. Just make sure to follow instructions on cloudera VM config based on inputs in the forum. Hopefully the contents and tools will get updated.
The precise definitions for many commonly used terms were very helpful. You do not find these details in many books or documents. Also, using KNIME was also interesting
Reasonable overview. The VM environment is a major challenge for my hardware. Takes more time to make it work than it should. I am wondering if a cloud solution e.g. GCP would be better.
This is a valuable course in learning the basics of machine learning. but I was hoping to to get more hands on practice in this course. but overall, i learned a lot with the existing content.
À propos du Spécialisation Big Data
Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.

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