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Chatbot is to engage with the customers in order to boost their business growth by using NLP and Speech Recognition. The chatbot is very helpful for its 24/7 presence and ability to reply instantly.
Cardiovascular diseases are the leading cause of death globally. It is therefore necessary to identify the causes, developing a system to predict heart attacks in an effective manner.
For some companies correctly predicting whether or not a loan will be a default and it is very important. Using historical data, developing a deep learning model to predict the chance of default for future loans.
Developing a model using a convolutional neural network that can classify lung infection in a person using medical imagery.
Future customizations, such as understanding human emotions, could lead to a range of advancementssuch as determining whether a person likes a specific statement, item or product, food, or how they are feeling in a particular circumstance, and so on. Building a model using a convolutional neural network that can classify a person's emotion
Developing a CNN model using distributed training that can detect diabetic retinopathy and deploy it using TensorFlow Serving.
Using a deep convolutional neural network (CNN) to perform facial recognition using Keras.
Preparing an agent by implementing Deep Q-Learning that can perform unsupervised trading in stock trade. The aim of this project is to train an agent that uses Q-learning and neural networks to predict the profit or loss by building a model and implementing it on a dataset that is available for evaluation.