{"product_id":"building-an-enterprise-chatbot-work-with-protected-enterprise-data-using-open-source-frameworks-paperback","title":"Building an Enterprise Chatbot: Work with Protected Enterprise Data Using Open Source Frameworks - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAbhishek Singh\u003c\/b\u003e (Author), \u003cb\u003eKarthik Ramasubramanian\u003c\/b\u003e (Author), \u003cb\u003eShrey Shivam\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eExplore the adoption of chatbots in business by focusing on the design, deployment, and continuous improvement of chatbots in a business, with a single use-case from the banking and insurance sector. This book starts by identifying the business processes in the banking and insurance industry. This involves data collection from sources such as conversations from customer service centers, online chats, emails, and other NLP sources. You'll then design the solution architecture of the chatbot. Once the architecture is framed, the author goes on to explain natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) with examples. \u003cbr\u003e\u003c\/p\u003e\u003cp\u003eIn the next sections, you'll design and implement the backend framework of a typical chatbot from scratch. You will also explore some popular open-source chatbot frameworks such as Dialogflow and LUIS. The authors then explain how you can integrate various third-party services and enterprise databases with the custom chatbot framework. In the final section, you'll discuss how to deploy the custom chatbot framework on the AWS cloud.\u003c\/p\u003e\u003cbr\u003eBy the end of \u003ci\u003eBuilding an Enterprise Chatbot\u003c\/i\u003e, you will be able to design and develop an enterprise-ready conversational chatbot using an open source development platform to serve the end user.\u003cbr\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003eIdentify business processes where chatbots could be used\u003c\/li\u003e\n\u003cli\u003eFocus on building a chatbot for one industry and one use-case rather than building a ubiquitous and generic chatbot \u003c\/li\u003e\n\u003cli\u003eDesign the solution architecture for a chatbot\u003c\/li\u003e\n\u003cli\u003eIntegrate chatbots with internal data sources using APIs\u003c\/li\u003e\n\u003cli\u003eDiscover the differences between natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) \u003c\/li\u003e\n\u003cli\u003eWork with deployment and continuous improvement through representational learning\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003e\u003cbr\u003e\u003c\/b\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003eData scientists and enterprise architects who are currently looking to deploy chatbot solutions to their business.\u003cbr\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eExplore the adoption of chatbots in business by focusing on the design, deployment, and continuous improvement of chatbots in a business, with a single use-case from the banking and insurance sector. This book starts by identifying the business processes in the banking and insurance industry. This involves data collection from sources such as conversations from customer service centers, online chats, emails, and other NLP sources. You'll then design the solution architecture of the chatbot. Once the architecture is framed, the author goes on to explain natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) with examples. \u003cbr\u003eIn the next section, you'll discuss the importance of data transfers using natural language platforms, such as Dialogflow and LUIS, and see why this is a key process for chatbot development. In the final section, you'll work with the RASA and Botpress frameworks. \u003cbr\u003eBy the end of \u003ci\u003eBuilding an Enterprise Chatbot with Python\u003c\/i\u003e, you will be able to design and develop an enterprise-ready conversational chatbot using an open source development platform to serve the end user.\u003cbr\u003eYou will: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eIdentify business processes \u003c\/li\u003e\n\u003cli\u003eDesign the solution architecture for a chatbot\u003c\/li\u003e\n\u003cli\u003eIntegrate chatbots with internal data sources using APIs\u003c\/li\u003e\n\u003cli\u003eDiscover the differences between natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) \u003c\/li\u003e\n\u003cli\u003eWork with deployment and continuous improvement through representational learning\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAbhishek Singh\u003c\/b\u003e is on a mission to profess the de facto language of this millennium, the numbers. He is on a journey to bring machines closer to humans, for a better and more beautiful world by generating opportunities with artificial intelligence and machine learning. He leads a team of data science professionals solving pressing problems in food security, cyber security, natural disasters, healthcare, and many more areas, all with the help of data and technology. Abhishek is in the process of bringing smart IoT devices to smaller cities in India so that people can leverage technology for the betterment of life.\u003c\/p\u003e \u003cp\u003eHe has worked with colleagues from many parts of the United States, Europe, and Asia, and strives to work with more people from various backgrounds. In 7 years at big corporations, he has stress-tested the assets of U.S. banks at Deloitte, solved insurance pricing models at Prudential, and made telecom experiences easier for customers at Celcom, and core SaaS Data products at Probyto. He is now creating data science opportunities with his team of young minds.\u003c\/p\u003e \u003cp\u003eHe actively participates in analytics-related thought leadership, authoring, public speaking, meetups, and training in data science. He is a staunch supporter of responsible use of AI to remove biases and fair use of AI for a better society.\u003c\/p\u003e \u003cp\u003eAbhishek completed his MBA from IIM Bangalore, a B.Tech. In Mathematics and Computing from IITGuwahati, and a PG Diploma in Cyber Law from NALSAR University, Hyderabad.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eKarthik Ramasubramanian\u003c\/b\u003e has over seven years of practice and leading Data Science and Business Analytics in Retail, FMCG, E-Commerce, Information Technology for a multi-national and two unicorn startups. A researcher and problem solver with a diverse set of experience in the data science lifecycle, starting from a data problem discovery to creating a data science prototype\/product. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e On the descriptive side of data science, designed, developed and spearheaded many A\/B experiment frameworks for improving product features, conceptualized funnel analysis for understanding user interactions and identifying the friction points within a product, designing statistically robust metrics and visual dashboards. On the predictive side, developed intelligent chatbots which understand human-like interactions, customer segmentation models, recommendation systems, identifying medical specialization from a patient query for telemedicine, and many more. \u003cp\u003e\u003c\/p\u003e He actively participates in analytics related thought leadership, authoring blogs \u0026amp; books, public speaking, meet-ups, and training \u0026amp; mentoring for Data Science.\u003cp\u003e\u003c\/p\u003e Karthik completed his M.Sc. in Theoretical Computer Science at PSG College of Technology, India, where he pioneered the application of machine learning, data mining, and fuzzy logic in his research work on the computer and network security.\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eShrey Shivam \u003c\/b\u003eextensive experience in leading the design, development, and delivery of solutions in the field of data engineering, stream analytics, machine learning, graph databases, and natural language processing. In his seven years of experience, he has worked with various conglomerates, startups, and big corporations and has gained relevant exposure to digital media, e-commerce, investment banking, insurance, and a suite of transaction-led marketplaces across music, food, lifestyle, news, legal and travel.\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003eHe is a keen learner and is actively engaged in designing the next generation of systems powered by artificial intelligence-based analytical and predictive models. He has taken up various roles in product management, data analytics, digital growth, system architecture, and full stack engineering. In the era of rapid acceptance and adoption of new and emerging technologies, he believes in strong technical fundamentals and advocates continuous improvement through self-learning.\u003cp\u003e \u003c\/p\u003e\u003cp\u003eShrey is currently leading a team of machine learning \u0026amp; big data engineers across the US, Europe, and India to build robust and scalable big data pipelines to implement various statistical and predictive models. Shrey has completed his BTech in Information Technology from Cochin University of Science Technology, India.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 385\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.84 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 13, 2019\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47212688507129,"sku":"9781484250334","price":70.18,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/dmtwUVI2dnhSQnBZMlpOcjFldlk0Zz09.webp?v=1768095038","url":"https:\/\/bookscloud.io\/products\/building-an-enterprise-chatbot-work-with-protected-enterprise-data-using-open-source-frameworks-paperback","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}