Engineering and Technology
Learn a variety of feature engineering techniques to develop meaningful features that will uncover useful insights about your machine learning models.
Feature engineering is a crucial step in the machine learning process that enables the discovery of valuable insights from models. This iterative process involves the creation of new features using existing variables, thereby enhancing the efficiency of the model. In this course, participants will have the opportunity to delve into various datasets and gain hands-on experience in applying diverse feature engineering techniques to both continuous and discrete variables.
by DataCamp
Learn a variety of feature engineering techniques to develop meaningful features that will uncover u...
by DataCamp
Learn about the difference between batching and streaming, scaling streaming systems, and real-world...
by DataCamp
Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.
by DataCamp
Explore a range of programming paradigms, including imperative and declarative, procedural, function...
by DataCamp
Julia is a new programming language designed to be the ideal language for scientific computing, mach...
by DataCamp
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
by DataCamp
Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb...
by DataCamp
Create interactive data visualizations in Python using Plotly.
by DataCamp
Learn to manipulate and analyze flexibly structured data with MongoDB.
by DataCamp
Begin your journey with Scala, a popular language for scalable applications and data engineering inf...