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Solve the most crucial business problem for a leading telecom operator in India and southeast Asia - predicting customer churn.
Learners will apply Q-Learning to train an RL agent to play the game of numerical Tic Tac Toe.
Create a solution that will help in identifying the type of complaint ticket raised by the customers of a multinational bank.
Build a machine learning model capable of detecting fraudulent transactions. Here you have to predict fraudulent credit card transactions with the help of machine learning models.
Build a neural network from scratch in Tensorflow to identify the type of skin cancer from image.
Make a Smart TV system which can control the TV with user’s hand gestures as the remote control.
Build a model to using the concepts of natural language processing and recommender systems to recommend news stories to users on a popular news platform.
Learners will use the Markov Decision Process & Q-Learning to build an RL agent that learns to choose the best request so as to maximize the total profit earned by the agent that day.
You will build a custom NER to get the list of diseases and their treatment from a medical healthcare dataset.
Build a model that can help any visually impaired person in understanding image present before them. It is a deep learning model which can explain the content of an image in the form of speech.
Build a sentiment analysis based product recommendation system to recommend the similar products to the users. Sentiment analysis is used to fine tune the product recommendation system.
Predict the sales for a european pharma giant using a host of different types of variables. Apply VAR and VARMAX models to build the appropriate model.
Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa. CycleGAN model is used for producing T2 type MRI images given T1 type input MRI images.
You will build an attention-based neural machine translation model translating from one language to another.
Create a custom object detector using the YOLO algorithm to detect the presence of face masks in the images of different people.