Keras is an incredible library to implement deep learning models. It acts as a wrapper for theano and tensorflow. Thanks to keras we can create powerful and complex deep learning models with only a few lines of code.Cognitive learning pdf this is what will allow you to have a global vision of what you are creating. Everything you make will look so clear and structured thanks to this library, that you will really get the intuition and understanding of what you are doing.Cognitive learning pdf

If you are just starting out into deep learning, then you will find this course extremely useful. Deep learning A-Z™ is structured around special coding blueprint approaches meaning that you won’t get bogged down in unnecessary programming or mathematical complexities and instead you will be applying deep learning techniques from very early on in the course. You will build your knowledge from the ground up and you will see how with every tutorial you are getting more and more confident.Cognitive learning pdf

If you already have experience with deep learning, you will find this course refreshing, inspiring and very practical. Inside deep learning A-Z™ you will master some of the most cutting-edge deep learning algorithms and techniques (some of which didn’t even exist a year ago) and through this course you will gain an immense amount of valuable hands-on experience with real-world business challenges.Cognitive learning pdf plus, inside you will find inspiration to explore new deep learning skills and applications.

In this part you will be solving a data analytics challenge for a bank.Cognitive learning pdf you will be given a dataset with a large sample of the bank’s customers. To make this dataset, the bank gathered information such as customer id, credit score, gender, age, tenure, balance, if the customer is active, has a credit card, etc.Cognitive learning pdf during a period of 6 months, the bank observed if these customers left or stayed in the bank.

Your goal is to make an artificial neural network that can predict, based on geo-demographical and transactional information given above, if any individual customer will leave the bank or stay (customer churn).Cognitive learning pdf besides, you are asked to rank all the customers of the bank, based on their probability of leaving. To do that, you will need to use the right deep learning model, one that is based on a probabilistic approach.Cognitive learning pdf

In this part, you will create a convolutional neural network that is able to detect various objects in images. We will implement this deep learning model to recognize a cat or a dog in a set of pictures.Cognitive learning pdf however, this model can be reused to detect anything else and we will show you how to do it – by simply changing the pictures in the input folder.Cognitive learning pdf

The branch of deep learning which facilitates this is recurrent neural networks. Classic rnns have short memory, and were neither popular nor powerful for this exact reason.Cognitive learning pdf but a recent major improvement in recurrent neural networks gave rise to the popularity of lstms (long short term memory rnns) which has completely changed the playing field. We are extremely excited to include these cutting-edge deep learning methods in our course!Cognitive learning pdf

Your final recommender system will be able to predict the ratings of the movies the customers didn’t watch. Accordingly, by ranking the predictions from 5 down to 1, your deep learning model will be able to recommend which movies each user should watch.Cognitive learning pdf creating such a powerful recommender system is quite a challenge so we will give ourselves two shots. Meaning we will build it with two different deep learning models.Cognitive learning pdf

And you will even be able to apply it to yourself or your friends. The list of movies will be explicit so you will simply need to rate the movies you already watched, input your ratings in the dataset, execute your model and voila!Cognitive learning pdf the recommender system will tell you exactly which movies you would love one night you if are out of ideas of what to watch on netflix!