[PDF] Practical Data Analytics For Bfsi Leveraging Data Science For Driving Decisions In Banking Financial Services And Insurance Operations - eBooks Review

Practical Data Analytics For Bfsi Leveraging Data Science For Driving Decisions In Banking Financial Services And Insurance Operations


Practical Data Analytics For Bfsi Leveraging Data Science For Driving Decisions In Banking Financial Services And Insurance Operations
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Practical Data Analytics For Bfsi Leveraging Data Science For Driving Decisions In Banking Financial Services And Insurance Operations


Practical Data Analytics For Bfsi Leveraging Data Science For Driving Decisions In Banking Financial Services And Insurance Operations
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Author : Bharat Sikka
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2023-09-02

Practical Data Analytics For Bfsi Leveraging Data Science For Driving Decisions In Banking Financial Services And Insurance Operations written by Bharat Sikka and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-02 with Computers categories.


Revolutionizing BFSI with Data Analytics Key Features ● Real-world examples and exercises will ground you in the practical application of analytics techniques specific to BFSI. ● Master Python for essential coding, SQL for data manipulation, and industry-leading tools like IBM SPSS and Power BI for sophisticated analyses. ● Understand how data-driven strategies generate profits, mitigate risks, and redefine customer support dynamics within the BFSI sphere. Book Description Are you looking to unlock the transformative potential of data analytics in the dynamic world of Banking, Financial Services, and Insurance (BFSI)? This book is your essential guide to mastering the intricate interplay of data science and analytics that underpins the BFSI landscape. Designed for intermediate-level practitioners, as well as those aspiring to join the ranks of BFSI analytics professionals, this book is your compass in the data-driven realm of banking. Address the unique challenges and opportunities of the BFSI sector using Artificial Intelligence and Machine Learning models for a data driven analysis. What you will learn ● Delve into the world of Data Science, including Artificial Intelligence and Machine Learning, with a focus on their application within BFSI. ● Explore hands-on examples and step-by-step tutorials that provide practical solutions to real-world challenges faced by banking institutions. ● Develop skills in essential programming languages such as Python (fundamentals) and SQL (intermediate), crucial for effective data manipulation and analysis. ● Gain insights into how businesses adapt data-driven strategies to make informed decisions, leading to improved operational efficiency. Who is this book for? This book is tailored for professionals already engaged in or seeking roles within Data Analytics in the BFSI industry. Additionally, it serves as a strategic resource for business leaders and upper management, guiding them in shaping data platforms and products within their organizations. Table of Contents 1. Introduction to BFSI and Data Driven Banking 2. Introduction to Analytics and Data Science 3. Major Areas of Analytics Utilization 4. Understanding Infrastructures behind BFSI for Analytics 5. Data Governance and AI/ML Model Governance in BFSI 6. Domains of BFSI and team planning 7. Customer Demographic Analysis and Customer Segmentation 8. Text Mining and Social Media Analytics 9. Lead Generation Through Analytical Reasoning and Machine Learning 10. Cross Sell and Up Sell of Products through Machine Learning 11. Pricing Optimization 12. Data Envelopment Analysis 13. ATM Cash Forecasting 14. Unstructured Data Analytics 15. Fraud Modelling 16. Detection of Money Laundering and Analysis 17. Credit Risk and Stressed Assets 18. High Performance Architectures: On-Premises and Cloud 19. Growing Trends in the Data-Driven Future of BFSI Index



Elements Of Deep Learning For Computer Vision


Elements Of Deep Learning For Computer Vision
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Author : Bharat Sikka
language : en
Publisher: BPB Publications
Release Date : 2021-06-24

Elements Of Deep Learning For Computer Vision written by Bharat Sikka and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-24 with Computers categories.


Conceptualizing deep learning in computer vision applications using PyTorch and Python libraries. KEY FEATURES ● Covers a variety of computer vision projects, including face recognition and object recognition such as Yolo, Faster R-CNN. ● Includes graphical representations and illustrations of neural networks and teaches how to program them. ● Includes deep learning techniques and architectures introduced by Microsoft, Google, and the University of Oxford. DESCRIPTION Elements of Deep Learning for Computer Vision gives a thorough understanding of deep learning and provides highly accurate computer vision solutions while using libraries like PyTorch. This book introduces you to Deep Learning and explains all the concepts required to understand the basic working, development, and tuning of a neural network using Pytorch. The book then addresses the field of computer vision using two libraries, including the Python wrapper/version of OpenCV and PIL. After establishing and understanding both the primary concepts, the book addresses them together by explaining Convolutional Neural Networks(CNNs). CNNs are further elaborated using top industry standards and research to explain how they provide complicated Object Detection in images and videos, while also explaining their evaluation. Towards the end, the book explains how to develop a fully functional object detection model, including its deployment over APIs. By the end of this book, you are well-equipped with the role of deep learning in the field of computer vision along with a guided process to design deep learning solutions. WHAT YOU WILL LEARN ● Get to know the mechanism of deep learning and how neural networks operate. ● Learn to develop a highly accurate neural network model. ● Access to rich Python libraries to address computer vision challenges. ● Build deep learning models using PyTorch and learn how to deploy using the API. ● Learn to develop Object Detection and Face Recognition models along with their deployment. WHO THIS BOOK IS FOR This book is for the readers who aspire to gain a strong fundamental understanding of how to infuse deep learning into computer vision and image processing applications. Readers are expected to have intermediate Python skills. No previous knowledge of PyTorch and Computer Vision is required. TABLE OF CONTENTS 1. An Introduction to Deep Learning 2. Supervised Learning 3. Gradient Descent 4. OpenCV with Python 5. Python Imaging Library and Pillow 6. Introduction to Convolutional Neural Networks 7. GoogLeNet, VGGNet, and ResNet 8. Understanding Object Detection 9. Popular Algorithms for Object Detection 10. Faster RCNN with PyTorch and YoloV4 with Darknet 11. Comparing Algorithms and API Deployment with Flask 12. Applications in Real World



Digital Transformation In Financial Services


Digital Transformation In Financial Services
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Author : Claudio Scardovi
language : en
Publisher: Springer
Release Date : 2018-08-15

Digital Transformation In Financial Services written by Claudio Scardovi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-15 with Business & Economics categories.


This book analyzes the set of forces driving the global financial system toward a period of radical transformation and explores the transformational challenges that lie ahead for global and regional or local banks and other financial intermediaries. It is explained how these challenges derive from the newly emerging post-crisis structure of the market and from shadow and digital players across all banking operations. Detailed attention is focused on the impacts of digitalization on the main functions of the financial system, and particularly the banking sector. The author elaborates how an alternative model of banking will enable banks to predict, understand, navigate, and change the external ecosystem in which they compete. The five critical components of this model are data and information mastering; effective use of applied analytics; interconnectivity and “junction playing”; development of new business solutions; and trust and credibility assurance. The analysis is supported by a number of informative case studies. The book will be of interest especially to top and middle managers and employees of banks and financial institutions but also to FinTech players and their advisers and others.



Building Cognitive Applications With Ibm Watson Services Volume 1 Getting Started


Building Cognitive Applications With Ibm Watson Services Volume 1 Getting Started
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Author : Dr. Alfio Gliozzo
language : en
Publisher: IBM Redbooks
Release Date : 2017-06-23

Building Cognitive Applications With Ibm Watson Services Volume 1 Getting Started written by Dr. Alfio Gliozzo and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-23 with Computers categories.


The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 1, introduces cognitive computing, its motivating factors, history, and basic concepts. This volume describes the industry landscape for cognitive computing and introduces Watson, the cognitive computing offering from IBM. It also describes the nature of the question-answering (QA) challenge that is represented by the Jeopardy! quiz game and it provides a high-level overview of the QA system architecture (DeepQA), developed for Watson to play the game. This volume charts the evolution of the Watson Developer Cloud, from the initial DeepQA implementation. This book also introduces the concept of domain adaptation and the processes that must be followed to adapt the various Watson services to specific domains.



Spss In Simple Steps


Spss In Simple Steps
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Author : Kiran Pandya
language : en
Publisher:
Release Date :

Spss In Simple Steps written by Kiran Pandya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.


SPSS in Simple Steps is very useful for all students, researchers and faculty members who need to analyze quantitative data in their research work. The objective of the book is to help the students and researchers to undertake statistical analysis using PASW / SPSS software package. It is designed to be read in front of the computer screen. The book commences with an introduction to the PASW / SPSS software and provides a step-by-step approach for explaining procedures and executing PASW / SPSS commands. It provides a clear understanding of commands, procedures and functions required for carrying out statistical analysis. The book covers basic and essential features of PASW/SPSS.



Operations In Financial Services


Operations In Financial Services
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Author : Michael Pinedo
language : en
Publisher: Foundations and Trends in Technology, Information and Operations Management
Release Date : 2017-12-21

Operations In Financial Services written by Michael Pinedo and has been published by Foundations and Trends in Technology, Information and Operations Management this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-21 with Bank management categories.


Operations in Financial Services establishes a framework for this research area from an operations management perspective. The first section presents an introduction and provides an overview of the topic. The second section establishes links between the current state of the art in relevant areas of operations management and operations research and three of the more important aspects of operations in financial services - (i) financial product design and testing, (ii) process delivery design, and (iii) process delivery management. The third section focuses on the current issues that are important in the financial services operations area. These issues center primarily on mobile online banking and trading in a global environment. The fourth section discusses operational risk aspects of financial services. The final section concludes with a discussion on research directions that may become of interest in the future.



Big Data


Big Data
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Author :
language : en
Publisher:
Release Date : 2011

Big Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Competition, International categories.




The Robotic Process Automation Handbook


The Robotic Process Automation Handbook
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Author : Tom Taulli
language : en
Publisher: Apress
Release Date : 2020-02-28

The Robotic Process Automation Handbook written by Tom Taulli and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-28 with Computers categories.


While Robotic Process Automation (RPA) has been around for about 20 years, it has hit an inflection point because of the convergence of cloud computing, big data and AI. This book shows you how to leverage RPA effectively in your company to automate repetitive and rules-based processes, such as scheduling, inputting/transferring data, cut and paste, filling out forms, and search. Using practical aspects of implementing the technology (based on case studies and industry best practices), you’ll see how companies have been able to realize substantial ROI (Return On Investment) with their implementations, such as by lessening the need for hiring or outsourcing. By understanding the core concepts of RPA, you’ll also see that the technology significantly increases compliance – leading to fewer issues with regulations – and minimizes costly errors. RPA software revenues have recently soared by over 60 percent, which is the fastest ramp in the tech industry, and they are expected to exceed $1 billion by the end of 2019. It is generally seamless with legacy IT environments, making it easier for companies to pursue a strategy of digital transformation and can even be a gateway to AI. The Robotic Process Automation Handbook puts everything you need to know into one place to be a part of this wave. What You'll Learn Develop the right strategy and plan Deal with resistance and fears from employees Take an in-depth look at the leading RPA systems, including where they are most effective, the risks and the costs Evaluate an RPA system Who This Book Is For IT specialists and managers at mid-to-large companies



Where The Flowers Still Grow


Where The Flowers Still Grow
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Author : Bharat Sikka
language : en
Publisher:
Release Date : 2017-09-15

Where The Flowers Still Grow written by Bharat Sikka and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-15 with categories.




Prominent Feature Extraction For Sentiment Analysis


Prominent Feature Extraction For Sentiment Analysis
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Author : Basant Agarwal
language : en
Publisher: Springer
Release Date : 2015-12-14

Prominent Feature Extraction For Sentiment Analysis written by Basant Agarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-14 with Medical categories.


The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.