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    Machine Learning for Finance Saurav Singla

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Machine Learning for Finance Saurav Singla - okladka książki

    Machine Learning for Finance Saurav Singla - okladka książki

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    Autor:
    Saurav Singla
    Wydawnictwo:
    BPB Publications (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    240
    Dostępne formaty:
         ePub
         Mobi
    Understand the essentials of Machine Learning and its impact in financial sector
    Key Features
  1. Explore the spectrum of machine learning and its usage.
  2. Understand the NLP and Computer Vision and their use cases.
  3. Understand the Neural Network, CNN, RNN and their applications.
  4. Understand the Reinforcement Learning and their applications.
  5. Learn the rising application of Machine Learning in the Finance sector.
  6. Exposure to data mining, data visualization and data analytics.

    Description
    The fields of machining adapting, profound learning, and computerized reasoning are quickly extending and are probably going to keep on doing as such for a long time to come. There are many main impetuses for this, as quickly caught in this review. Now and again, the advancement has been emotional, opening new ways to deal with long-standing innovation challenges, for example, progresses in PC vision and picture investigation.

    The book demonstrates how to solve some of the most common issues in the financial industry. The book addresses real-life problems faced by practitioners on a daily basis. The book explains how machine learning works on structured data, text, and images. You will cover the exploration of Nave Bayes, Normal Distribution, Clustering with Gaussian process, advanced neural network, sequence modeling, and reinforcement learning. Later chapters will discuss machine learning use cases in the finance sector and the implications of deep learning. The book ends with traditional machine learning algorithms.

    Machine Learning has become very important in the finance industry, which is mostly used for better risk management and risk analysis. Better analysis leads to better decisions which lead to an increase in profit for financial institutions. Machine Learning to empower fintech to make massive profits by optimizing processes, maximizing efficiency, and increasing profitability.

    What will you learn
  7. You will grasp the most relevant techniques of Machine Learning for everyday use.
  8. You will be confident in building and implementing ML algorithms.
  9. Familiarize the adoption of Machine Learning for your business need.
  10. Discover more advanced concepts applied in banking and other sectors today.
  11. Build mastery skillset in designing smart AI applications including NLP, Computer Vision and Deep Learning.

    Who this book is for
    Data Scientist, Machine Learning Engineers and Individuals who want to adopt machine learning in the financial domain. Practitioners are working in banks, asset management, hedge funds or working the first time in the finance domain. Individuals who want to learn about applications of machine learning in finance or individuals entering the fintech domain.

    Table of Contents
    1.Introduction
    2.Naive Bayes, Normal Distribution and Automatic Clustering Processes
    3.Machine Learning for Data Structuring
    4.Parsing Data Using NLP
    5.Computer Vision
    6.Neural Network, GBM and Gradient Descent
    7.Sequence Modeling
    8.Reinforcement Learning For Financial Markets
    9.Finance Use Cases
    10.Impact of Machine Learning on Fintech
    11.Machine Learning in Finance
    12.eKYC and Anti-Fraud Policy
    13.Uses of Data Mining and Data Visualization
    14.Advantages and Disadvantages of Machine Learning
    15.Applications of Machine Learning in Other Industries
    16.Ethical considerations in Artificial Intelligence
    17.Artificial Intelligence in Banking
    18.Common Machine Learning Algorithms
    19.Frequently Asked Questions

    About the Author
    SAURAV SINGLA Saurav is a high performing Senior Data Scientist with 15 years of deep expertise in the application of analytics, business intelligence, machine learning, and statistics in multiple industries and 3 years of consulting experience and 5 years of managing a team in the data science field. He is a creative problem solver with a unique mix of technical, business, and research proficiency that lends itself to developing key strategies and solutions with a significant impact on revenue and ROI. He has working experience in machine learning, statistics, natural language processing, and deep learning with extensive use of Python, R, SQL & Tableau.


    LinkedIn Profile: https://www.linkedin.com/in/saurav-singla-5b412320/

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