Sculpting Data For Ml

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Sculpting Data for ML

Author : Rishabh Misra
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.5/5 (854 download)

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Book Synopsis Sculpting Data for ML by : Rishabh Misra

Download or read book Sculpting Data for ML written by Rishabh Misra and published by . This book was released on 2021-01-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the contemporary world of Artificial Intelligence and Machine Learning, data is the new oil. For Machine Learning algorithms to work their magic, it is imperative to lay a firm foundation with relevant data. Sculpting Data for ML introduces the readers to the first act of Machine Learning, Dataset Curation. This book puts forward practical tips to identify valuable information from the extensive amount of crude data available at our fingertips. The step-by-step guide accompanies code examples in Python from the extraction of real-world datasets and illustrates ways to hone the skills of extracting meaningful datasets. In addition, the book also dives deep into how data fits into the Machine Learning ecosystem and tries to highlight the impact good quality data can have on the Machine Learning system's performance. What's Inside? * Significance of data in Machine Learning * Identification of relevant data signals * End-to-end process of data collection and dataset construction * Overview of extraction tools like BeautifulSoup and Selenium * Step-by-step guide with Python code examples of real-world use cases * Synopsis of Data Preprocessing and Feature Engineering techniques * Introduction to Machine Learning paradigms from a data perspective This book is for Machine Learning researchers, practitioners, or enthusiasts who want to tackle the data availability challenges to address real-world problems. The authors Jigyasa Grover & Rishabh Misra are Machine Learning Engineers by profession and are passionate about tackling real-world problems leveraging their data curation and ML expertise. The book is endorsed by leading ML experts from both academia and industry. It has forewords by: * Julian McAuley, Associate Professor at University of California San Diego * Laurence Moroney, Lead Artificial Intelligence Advocate at Google * Mengting Wan, Senior Applied Scientist at Microsoft

Data Science Live Book

Author : Pablo Casas
Publisher :
ISBN 13 : 9789874273666
Total Pages : pages
Book Rating : 4.2/5 (736 download)

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Book Synopsis Data Science Live Book by : Pablo Casas

Download or read book Data Science Live Book written by Pablo Casas and published by . This book was released on 2018-03-16 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to problems that commonly arise when developing a machine learning project. The book's topics are: Exploratory data analysis Data Preparation Selecting best variables Assessing Model Performance More information on predictive modeling will be included soon. This book tries to demonstrate what it says with short and well-explained examples. This is valid for both theoretical and practical aspects (through comments in the code). This book, as well as the development of a data project, is not linear. The chapters are related among them. For example, the missing values chapter can lead to the cardinality reduction in categorical variables. Or you can read the data type chapter and then change the way you deal with missing values. You¿ll find references to other websites so you can expand your study, this book is just another step in the learning journey. It's open-source and can be found at http://livebook.datascienceheroes.com

The Routledge Companion to Artificial Intelligence in Architecture

Author : Imdat As
Publisher : Routledge
ISBN 13 : 1000372413
Total Pages : 632 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis The Routledge Companion to Artificial Intelligence in Architecture by : Imdat As

Download or read book The Routledge Companion to Artificial Intelligence in Architecture written by Imdat As and published by Routledge. This book was released on 2021-05-06 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing the most comprehensive source available, this book surveys the state of the art in artificial intelligence (AI) as it relates to architecture. This book is organized in four parts: theoretical foundations, tools and techniques, AI in research, and AI in architectural practice. It provides a framework for the issues surrounding AI and offers a variety of perspectives. It contains 24 consistently illustrated contributions examining seminal work on AI from around the world, including the United States, Europe, and Asia. It articulates current theoretical and practical methods, offers critical views on tools and techniques, and suggests future directions for meaningful uses of AI technology. Architects and educators who are concerned with the advent of AI and its ramifications for the design industry will find this book an essential reference.

The Artist in the Machine

Author : Arthur I. Miller
Publisher : MIT Press
ISBN 13 : 0262042851
Total Pages : 429 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Artist in the Machine by : Arthur I. Miller

Download or read book The Artist in the Machine written by Arthur I. Miller and published by MIT Press. This book was released on 2019-10-01 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authority on creativity introduces us to AI-powered computers that are creating art, literature, and music that may well surpass the creations of humans. Today's computers are composing music that sounds “more Bach than Bach,” turning photographs into paintings in the style of Van Gogh's Starry Night, and even writing screenplays. But are computers truly creative—or are they merely tools to be used by musicians, artists, and writers? In this book, Arthur I. Miller takes us on a tour of creativity in the age of machines. Miller, an authority on creativity, identifies the key factors essential to the creative process, from “the need for introspection” to “the ability to discover the key problem.” He talks to people on the cutting edge of artificial intelligence, encountering computers that mimic the brain and machines that have defeated champions in chess, Jeopardy!, and Go. In the central part of the book, Miller explores the riches of computer-created art, introducing us to artists and computer scientists who have, among much else, unleashed an artificial neural network to create a nightmarish, multi-eyed dog-cat; taught AI to imagine; developed a robot that paints; created algorithms for poetry; and produced the world's first computer-composed musical, Beyond the Fence, staged by Android Lloyd Webber and friends. But, Miller writes, in order to be truly creative, machines will need to step into the world. He probes the nature of consciousness and speaks to researchers trying to develop emotions and consciousness in computers. Miller argues that computers can already be as creative as humans—and someday will surpass us. But this is not a dystopian account; Miller celebrates the creative possibilities of artificial intelligence in art, music, and literature.

An Intuitive Exploration of Artificial Intelligence

Author : Simant Dube
Publisher : Springer Nature
ISBN 13 : 3030686248
Total Pages : 355 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis An Intuitive Exploration of Artificial Intelligence by : Simant Dube

Download or read book An Intuitive Exploration of Artificial Intelligence written by Simant Dube and published by Springer Nature. This book was released on 2021-06-21 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.

Principles of Data Science

Author : Sinan Ozdemir
Publisher : Packt Publishing Ltd
ISBN 13 : 1837636001
Total Pages : 326 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis Principles of Data Science by : Sinan Ozdemir

Download or read book Principles of Data Science written by Sinan Ozdemir and published by Packt Publishing Ltd. This book was released on 2024-01-31 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your data Key Features Learn practical data science combined with data theory to gain maximum insights from data Discover methods for deploying actionable machine learning pipelines while mitigating biases in data and models Explore actionable case studies to put your new skills to use immediately Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPrinciples of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights. Starting with cleaning and preparation, you’ll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you’ll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data. With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You’ll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you’ll explore medium-level data governance, including data provenance, privacy, and deletion request handling. By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT.What you will learn Master the fundamentals steps of data science through practical examples Bridge the gap between math and programming using advanced statistics and ML Harness probability, calculus, and models for effective data control Explore transformative modern ML with large language models Evaluate ML success with impactful metrics and MLOps Create compelling visuals that convey actionable insights Quantify and mitigate biases in data and ML models Who this book is for If you are an aspiring novice data scientist eager to expand your knowledge, this book is for you. Whether you have basic math skills and want to apply them in the field of data science, or you excel in programming but lack the necessary mathematical foundations, you’ll find this book useful. Familiarity with Python programming will further enhance your learning experience.

Data Engineering for AI/ML Pipelines

Author : Venkata Karthik Penikalapati
Publisher : BPB Publications
ISBN 13 : 9365899036
Total Pages : 316 pages
Book Rating : 4.3/5 (658 download)

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Book Synopsis Data Engineering for AI/ML Pipelines by : Venkata Karthik Penikalapati

Download or read book Data Engineering for AI/ML Pipelines written by Venkata Karthik Penikalapati and published by BPB Publications. This book was released on 2024-10-18 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: DESCRIPTION Data engineering is the art of building and managing data pipelines that enable efficient data flow for AI/ML projects. This book serves as a comprehensive guide to data engineering for AI/ML systems, equipping you with the knowledge and skills to create robust and scalable data infrastructure. This book covers everything from foundational concepts to advanced techniques. It begins by introducing the role of data engineering in AI/ML, followed by exploring the lifecycle of data, from data generation and collection to storage and management. Readers will learn how to design robust data pipelines, transform data, and deploy AI/ML models effectively for real-world applications. The book also explains security, privacy, and compliance, ensuring responsible data management. Finally, it explores future trends, including automation, real-time data processing, and advanced architectures, providing a forward-looking perspective on the evolution of data engineering. By the end of this book, you will have a deep understanding of the principles and practices of data engineering for AI/ML. You will be able to design and implement efficient data pipelines, select appropriate technologies, ensure data quality and security, and leverage data for building successful AI/ML models. KEY FEATURES ● Comprehensive guide to building scalable AI/ML data engineering pipelines. ● Practical insights into data collection, storage, processing, and analysis. ● Emphasis on data security, privacy, and emerging trends in AI/ML. WHAT YOU WILL LEARN ● Architect scalable data solutions for AI/ML-driven applications. ● Design and implement efficient data pipelines for machine learning. ● Ensure data security and privacy in AI/ML systems. ● Leverage emerging technologies in data engineering for AI/ML. ● Optimize data transformation processes for enhanced model performance. WHO THIS BOOK IS FOR This book is ideal for software engineers, ML practitioners, IT professionals, and students wanting to master data pipelines for AI/ML. It is also valuable for developers and system architects aiming to expand their knowledge of data-driven technologies. TABLE OF CONTENTS 1. Introduction to Data Engineering for AI/ML 2. Lifecycle of AI/ML Data Engineering 3. Architecting Data Solutions for AI/ML 4. Technology Selection in AI/ML Data Engineering 5. Data Generation and Collection for AI/ML 6. Data Storage and Management in AI/ML 7. Data Ingestion and Preparation for ML 8. Transforming and Processing Data for AI/ML 9. Model Deployment and Data Serving 10. Security and Privacy in AI/ML Data Engineering 11. Emerging Trends and Future Direction

AI-Assisted Programming

Author : Tom Taulli
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098164520
Total Pages : 231 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis AI-Assisted Programming by : Tom Taulli

Download or read book AI-Assisted Programming written by Tom Taulli and published by "O'Reilly Media, Inc.". This book was released on 2024-04-10 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. This book examines: The core capabilities of AI-based development tools Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer Ways to use ChatGPT, Gemini, Claude, and other generic LLMs for coding Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing Prompt engineering for development Using AI-assisted programming for tedious tasks like creating regular expressions, starter code, object-oriented programming classes, and GitHub Actions How to use AI-based low-code and no-code tools, such as to create professional UIs

Surfing Uncertainty

Author : Andy Clark
Publisher : Oxford University Press, USA
ISBN 13 : 0190217014
Total Pages : 425 pages
Book Rating : 4.1/5 (92 download)

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Book Synopsis Surfing Uncertainty by : Andy Clark

Download or read book Surfing Uncertainty written by Andy Clark and published by Oxford University Press, USA. This book was released on 2016 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exciting new theories in neuroscience, psychology, and artificial intelligence are revealing minds like ours as predictive minds, forever trying to guess the incoming streams of sensory stimulation before they arrive. In this up-to-the-minute treatment, philosopher and cognitive scientist Andy Clark explores new ways of thinking about perception, action, and the embodied mind.

Machine Learning and Security

Author : Clarence Chio
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491979852
Total Pages : 394 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Machine Learning and Security by : Clarence Chio

Download or read book Machine Learning and Security written by Clarence Chio and published by "O'Reilly Media, Inc.". This book was released on 2018-01-26 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions

Complex Networks XV

Author : Federico Botta
Publisher : Springer Nature
ISBN 13 : 3031575156
Total Pages : 222 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Complex Networks XV by : Federico Botta

Download or read book Complex Networks XV written by Federico Botta and published by Springer Nature. This book was released on with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning in Finance

Author : Matthew F. Dixon
Publisher : Springer Nature
ISBN 13 : 3030410684
Total Pages : 565 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning in Finance by : Matthew F. Dixon

Download or read book Machine Learning in Finance written by Matthew F. Dixon and published by Springer Nature. This book was released on 2020-07-01 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.

Data Protection in a Post-Pandemic Society

Author : Chaminda Hewage
Publisher : Springer Nature
ISBN 13 : 303134006X
Total Pages : 246 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Data Protection in a Post-Pandemic Society by : Chaminda Hewage

Download or read book Data Protection in a Post-Pandemic Society written by Chaminda Hewage and published by Springer Nature. This book was released on 2023-07-11 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers the latest research results and predictions in data protection with a special focus on post-pandemic society. This book also includes various case studies and applications on data protection. It includes the Internet of Things (IoT), smart cities, federated learning, Metaverse, cryptography and cybersecurity. Data protection has burst onto the computer security scene due to the increased interest in securing personal data. Data protection is a key aspect of information security where personal and business data need to be protected from unauthorized access and modification. The stolen personal information has been used for many purposes such as ransom, bullying and identity theft. Due to the wider usage of the Internet and social media applications, people make themselves vulnerable by sharing personal data. This book discusses the challenges associated with personal data protection prior, during and post COVID-19 pandemic. Some of these challenges are caused by the technological advancements (e.g. Artificial Intelligence (AI)/Machine Learning (ML) and ChatGPT). In order to preserve the privacy of the data involved, there are novel techniques such as zero knowledge proof, fully homomorphic encryption, multi-party computations are being deployed. The tension between data privacy and data utility drive innovation in this area where numerous start-ups around the world have started receiving funding from government agencies and venture capitalists. This fuels the adoption of privacy-preserving data computation techniques in real application and the field is rapidly evolving. Researchers and students studying/working in data protection and related security fields will find this book useful as a reference.

AI and Its Convergence With Communication Technologies

Author : Muneer, Badar
Publisher : IGI Global
ISBN 13 : 1668477033
Total Pages : 324 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis AI and Its Convergence With Communication Technologies by : Muneer, Badar

Download or read book AI and Its Convergence With Communication Technologies written by Muneer, Badar and published by IGI Global. This book was released on 2023-08-25 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The integration of Artificial Intelligence (AI) with Communication Technologies (ICT) is a critical aspect of research and development today, but it poses numerous challenges and bottlenecks. To address these issues, the book AI and Its Convergence with Communication Technologies, edited by a team of expert scholars, provides a comprehensive overview of the state-of-the-art research and practical challenges related to AI's convergence with ICT. It is designed to benefit engineers, professionals, scientists, and academicians, providing them with insights into the ICT industry and research from an AI perspective. The book covers a wide range of topics, including recent advancements and applications in AI, AI in signal processing, AI in mobile and modern wireless networks, and AI towards automation. It also addresses potential applications of AI in national defense, military technology, hybrid warfare, medical and health sciences, and energy-efficient systems. Furthermore, the book highlights the strengths and weaknesses of AI convergence with ICT, along with emerging frontiers and recommendations. It provides a brief history of AI in ICT and a comprehensive introduction to ICT-related methods and techniques in artificial intelligence and machine learning. The book emphasizes the role of AI in extracting knowledge and making predictions in decision-making strategies for businesses, management, and governance. Overall, this book offers a significant contribution to the understanding of AI and its convergence with communication technologies, making it a must-read for scholars and researchers who seek to understand the intersection of AI and ICT and how it impacts modern industries and research.

Sport Supplement Reference Guide

Author : William Llewellyn
Publisher : MOLECULAR NUTRITION LLC
ISBN 13 : 0967930480
Total Pages : 437 pages
Book Rating : 4.9/5 (679 download)

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Book Synopsis Sport Supplement Reference Guide by : William Llewellyn

Download or read book Sport Supplement Reference Guide written by William Llewellyn and published by MOLECULAR NUTRITION LLC. This book was released on 2009-10 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: William Llewellyn, the author of the best selling Anabolics series, brings you the most comprehensive book ever written on sport supplements. The Sport Supplement Reference Guide takes a look at over 40 of today's most popular sport supplement ingredients. What you can expect from Sport Supplement Reference Guide: • An overview of the sport supplement industry • Protein primer and how to choose the right type of protein for your needs. • Types of Carbohydrate Supplementation. • Vitamin and Mineral overview. • Supplement Ingredient Profiles of over 40 different ingredients. Each profile has its own rating based on clinical studies and empirical evidence. • Rules for Effective Supplement Shopping and Consumer Empowerment. This section will help you stop wasting money on worthless supplements. • Goal orientated sample supplement cycles takes the guess work out what supplements needed for your goal. This book is perfect for anyone that consumes dietary supplements for sports related activity, weight lifting, bodybuilding, weight loss, or other fitness goals.

Big Data Analytics

Author : Arun K. Somani
Publisher : CRC Press
ISBN 13 : 1315391244
Total Pages : 484 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Big Data Analytics by : Arun K. Somani

Download or read book Big Data Analytics written by Arun K. Somani and published by CRC Press. This book was released on 2017-10-30 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.

Learn Data Science from Scratch

Author : Pratheerth Padman
Publisher : BPB Publications
ISBN 13 : 9355517033
Total Pages : 344 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis Learn Data Science from Scratch by : Pratheerth Padman

Download or read book Learn Data Science from Scratch written by Pratheerth Padman and published by BPB Publications. This book was released on 2024-02-15 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Turn raw data into meaningful solutions KEY FEATURES ● Complete guide to master data science basics. ● Practical and hands-on examples in ML, deep learning, and NLP. ● Drive innovation and improve decision making through the power of data. DESCRIPTION Learn Data Science from Scratch equips you with the essential tools and techniques, from Python libraries to machine learning algorithms, to tackle real-world problems and make informed decisions. This book provides a thorough exploration of essential data science concepts, tools, and techniques. Starting with the fundamentals of data science, you will progress through data collection, web scraping, data exploration and visualization, and data cleaning and pre-processing. You will build the required foundation in statistics and probability before diving into machine learning algorithms, deep learning, natural language processing, recommender systems, and data storage systems. With hands-on examples and practical advice, each chapter offers valuable insights and key takeaways, empowering you to master the art of data-driven decision making. By the end of this book, you will be well-equipped with the essential skills and knowledge to navigate the exciting world of data science. You will be able to collect, analyze, and interpret data, build and evaluate machine learning models, and effectively communicate your findings, making you a valuable asset in any data-driven environment. WHAT YOU WILL LEARN ● Master key data science tools like Python, NumPy, Pandas, and more. ● Build a strong foundation in statistics and probability for data analysis. ● Learn and apply machine learning, from regression to deep learning. ● Expertise in NLP and recommender systems for advanced analytics. ● End-to-end data project from data collection to model deployment, with planning and execution. WHO THIS BOOK IS FOR This book is ideal for beginners with a basic understanding of programming, particularly in Python, and a foundational knowledge of mathematics. It is well-suited for aspiring data scientists and analysts. TABLE OF CONTENTS 1. Unraveling the Data Science Universe: An Introduction 2. Essential Python Libraries and Tools for Data Science 3. Statistics and Probability Essentials for Data Science 4. Data Mining Expedition: Web Scraping and Data Collection Techniques 5. Painting with Data: Exploration and Visualization 6. Data Alchemy: Cleaning and Preprocessing Raw Data 7. Machine Learning Magic: An Introduction to Predictive Modeling 8. Exploring Regression: Linear, Logistic, and Advanced Methods 9. Unveiling Patterns with k-Nearest Neighbors and Naïve Bayes 10. Exploring Tree-Based Models: Decision Trees to Gradient Boosting 11. Support Vector Machines: Simplifying Complexity 12. Dimensionality Reduction: From PCA to Advanced Methods 13. Unlocking Unsupervised Learning 14. The Essence of Neural Networks and Deep Learning 15. Word Play: Text Analytics and Natural Language Processing 16. Crafting Recommender Systems 17. Data Storage Mastery: Databases and Efficient Data Management 18. Data Science in Action: A Comprehensive End-to-end Project