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In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.
In this deep learning project, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset using Keras in Python.
In this deep learning project, we are going to predict which team will win the NCAA basketball tournament of coming 2017 based on past historical data.
AI, Machine Learning and Deep Learning are on the verge of innovating something that once upon a time seemed unthinkable. Deep learning is transforming heavily regulated industries like finance, trading, healthcare, and life sciences. For people who have not worked with Deep Learning yet, Keras library is good for a great start as it is designed for easy neural network assembly which comes with several pre-packaged network types like CNN’s in 2D and 3D flavours, long and short term neural networks and more general recurrent neural networks. Our expert panel suggests working with Keras Deep Learning library because implementing neural networks with Keras is straight-forward once you have determined what kind of neural network you want to build. Keras semantics are very layer-oriented that makes network assembly comparatively intuitive.
You will not regret working on these deep learning project suggestions. See what all you will learn –