Time to completeApprox. 4 hours
About this course
Ready to start your journey into Deep Learning with TensorFlow? In this course, you will learn how to create, train, and test a neural network in TensorFlow and Keras.
Skills you'll gain
Understand the math of deep learning
Build neural networks in TensorFlow
Create predictive regression models
Syllabus3 lessons • 1 projects • 1 quizzes
Hands-on learningDon’t just watch or read about someone else coding — write your own code live in our online, interactive platform. You’ll even get AI-driven recommendations on what you need to review to help keep you on track.
Projects in this course
Implementing Neural NetworksThe World Health Organization (WHO)'s Global Health Observatory (GHO) data repository tracks life expectancy for countries worldwide by following health status and many other related factors. Although there have been a lot of studies undertaken in the past on factors affecting life expectancy considering demographic variables, income composition, and mortality rates, it was found that the effects of immunization and human development index were not taken into account. This dataset covers a variety of indicators for all countries from 2000 to 2015 including: * immunization factors * mortality factors * economic factors * social factors * other health-related factors Ideally, this data will eventually inform countries concerning which factors to change in order to improve the life expectancy of their populations. If we can predict life expectancy well given all the factors, this is a good sign that there are some important patterns in the data. Life expectancy is expressed in years, and hence it is a number. This means that in order to build a predictive model one needs to use regression. In this project, you will design, train, and evaluate a neural network model performing the task of regression to predict the life expectancy of countries using this dataset. Excited? Let's go!
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