Mathematics and Statistics
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Linear regression and logistic regression are highly popular statistical models that serve as powerful tools for uncovering valuable insights within datasets. This comprehensive course equips you with the essential skills to effectively apply simple linear and logistic regressions. Through engaging hands-on exercises, you will delve into real-world datasets encompassing diverse domains such as motor insurance claims, Taiwan house prices, and fish sizes. By the conclusion of this course, you will possess the expertise to generate accurate predictions from your data, evaluate model performance, and identify potential issues with model fit.
by DataCamp
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regres...
by DataCamp
Learn to perform linear and logistic regression with multiple explanatory variables.
by DataCamp
Learn to perform linear and logistic regression with multiple explanatory variables.
by DataCamp
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regres...
by DataCamp
Learn to start developing deep learning models with Keras.
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Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
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Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.
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In this course you'll learn to use and present logistic regression models for making predictions.
by DataCamp
Learn the power of deep learning in PyTorch. Build your first neural network, adjust hyperparameters...
by DataCamp
Explore the concepts and applications of linear models with python and build models to describe, pre...