AutoKeras

Basic Deep Learning you own this product

This free project is part of the liveProject series Image Classification with AutoKeras

prerequisites: basic Python, pandas, Matplotlib, NumPy, SciPy, scikit-learn, and deep learning/Keras
skills learned: constructing deep learning models for image classification • search the hyperparameters of deep models with grid search and random search

Xiaotian Han

1 week · 4-6 hours per week · INTERMEDIATE

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Data Science

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liveProject

$19.49

liveProject This free project is part of the liveProject series Image Classification with AutoKeras liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. explore series

This free project is part of the liveProject series Image Classification with AutoKeras explore series

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In this liveProject, you’ll learn and apply some of the basics of deep learning in order to build the foundations of an AutoML image classifier. You’ll discover the basic deep learning models for image classification, and then experiment with tuning the hyperparameters of a convolutional neural network to improve your results.

project author

Xiaotian Han

Xiaotian Han is a Ph.D. student at Texas A&M University, where he works in the field of data mining and automated machine learning. He has published several research papers related to data mining and automated machine learning, and participated in an open-source package, AutoRec, which is highly based on the AutoKeras.

prerequisites

This liveProject is for Python programmers who know the basics of deep learning. To begin this liveProject, you will need to be familiar with the following:

TOOLS

TECHNIQUES

Basic deep learning/Keras

you will learn

This liveProject introduces the basics of traditional deep learning, as part of a journey into utilizing automated machine learning practices.

Constructing deep learning models for image classification
Search the hyperparameters of deep models with grid search and random search

features

Self-paced: You choose the schedule and decide how much time to invest as you build your project.
Project roadmap: Each project is divided into several achievable steps.
Get Help: While within the liveProject platform, get help from other participants.
Compare with others: For each step, compare your deliverable to the solutions by the author and other participants.