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Negotiation agent
Negor is an eCommerce AI chatbot that increases sales by engaging with the user much like a salesperson when you walk into a store. This conversational eCommerce approach allows companies to overcome sales obstacles, recommend products for cross- or up-sells, and reduce support tickets all while being available 24/7. E-commerce is a way to make the customers' buying experience more seamless and interactive while helping to offer bargaining features, which are familiar in traditional stores. In addition, the Chatbot is used to negotiate the best price for the customer and the best deal for the seller.
Hands-on question answering systems with BERT : Applications in neural networks and natural language processing
Begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. You will: Examine the fundamentals of word embeddings / Apply neural networks and BERT for various NLP tasks / Develop a question-answering system from scratch / Train question-answering systems for your own data
FitBuddy : An artificial intelligence powered personal trainer
FitBuddy App is a sports application that employs artificial intelligence in its job as a personal trainer that enables users to exercise anywhere with convenience, tremendous benefit, and high accuracy. The user can exercise with or without weights, in addition to cycling and running. The user must first provide the application with the personal data it has asked for in order to create an appropriate sports program for the user. After that, the user may explore the sports program's weeks and day's sections.
Error-Correction Coding and Decoding : Bounds, Codes, Decoders, Analysis and Applications
This book discusses both the theory and practical applications of self-correcting data, commonly known as error-correcting codes. The applications included demonstrate the importance of these codes in a wide range of everyday technologies, from smartphones to secure communications and transactions. Written in a readily understandable style,This book is a valuable resource for anyone interested in error-correcting codes and their applications, ranging from non-experts to professionals at the forefront of research in their field.
Dr.phone
Dr phone is a software system that helps in talking with the doctor automatically and easily without the need to go to the doctor's clinic to diagnose the patient's condition. our application presents an available platform to make a video call between the doctor and the patient according to the patient’s needs. The system accepts the patient’s request after choosing an available doctor andthen waits for the doctor to accept his request, if there is no doctor available, the system performs an AI chatbot to the patient's need to give him the appropriate diagnosis. when the call finished the doctor represents medical record including the medicine and the analytics and record the next appointment if it’s needed then send them to the patient's email, the patient also can see the nearest pharmacies or labs according to his location, and finally the patient rates the doctor after the call is finished then payment by his available wallet.
Deep learning approach for text summarization
Machine learning and deep learning, as we know, have started ruling over almost every field in the computing industry and so, has revolutionized the process of text summarization too. Automatic text summarization is an advancing realm of the natural language processing research in which concise textual summaries are generated from lengthy input documents. Extensive research has been carried out on how automatic summarization can be prosecuted through various extractive and abstractive techniques. In this paper, we address all the approaches to text summarization and present the modus operandi of an Architecture called Encoder Decoder, under the machine learning approach.
