4-Deep-Learning-Models :

1.Mobile Price Classification:

Mark has started his own mobile company. He wants to give tough fight to big companies like
Apple,Samsung etc. He does not know how to estimate price of mobiles his company creates. In this competitive mobile phone market you cannot simply assume things. To solve this problem he collects sales
data of mobile phones of various companies. Mark wants to find out some relation between features of a mobile phone (eg:- RAM,Internal
Memory etc) and its selling price. But he is not so good at Machine Learning. So he needs your
help to solve this problem. In this problem you do not have to predict actual price but a price range indicating how high the
price is. Developed a Deep Learning model using keras and Tensorflow framework to categorise the mobiles.

2.Product Name Identification:

Developed a Deep learning model using Fashion_Mnist dataset to identify and predict the various products that it contains. You can use the in built dataset found in Keras.datasets.

3.Penguin Species Classification:

The palmerpenguins data contains size measurements for three penguin species observed on three islands in the Palmer Archipelago, Antarctica. The physical attributes measured are flipper length, beak length, beak width, body mass, and sex. Developed a Deep learning model to predict the penguin species using attributes of the species.

4.Heart Disease Prediction:

This dataset heart.csv gives a number of variables along with a target condition of having or not having heart disease. developed a deep learning model using only Tensorflow to use this data to create a model which tries to predict if a patient has this disease or not.