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Unlock Your Data Superpowers: Master Data Science & ML with ChatGPT

Unlock Your Data Superpowers: Master Data Science & ML with ChatGPT
Author: Fredric Cardin
Publisher: DigitalSphere Creations
Total Pages: 66
Release:
Genre: Computers
ISBN:
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Ready to transform data into actionable insights? This comprehensive ebook equips you with the fundamentals of Data Science and Machine Learning, along with the game-changing power of ChatGPT. Inside, you'll discover: Core principles of Data Science and Machine Learning - the foundation for building powerful models. How to leverage ChatGPT's capabilities to streamline tasks and unlock new possibilities. Mastering Matplotlib and Seaborn - essential Python libraries for creating clear and impactful data visualizations. Building 3 complete Data Science and Machine Learning projects - get hands-on experience applying your newfound knowledge efficiently, guided by ChatGPT. This ebook is your roadmap to becoming a data pro, empowering you to: Make data-driven decisions with confidence Extract valuable insights from complex datasets Craft compelling data visualizations to communicate your findings Gain a competitive edge in the job market Don't wait - unlock your data superpowers today!

From Zero to Data Hero

From Zero to Data Hero
Author: Andrew Wu
Publisher:
Total Pages: 0
Release: 2023-11-05
Genre:
ISBN:
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Whether you're kickstarting your journey or deepening your expertise, this book unveils the power of ChatGPT's advanced tools for data analysis, visualization, machine learning, and even the nuances of deep learning.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
Total Pages: 385
Release: 2020-06-21
Genre: Computers
ISBN: 0128184396
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Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Data Scientists at Work

Data Scientists at Work
Author: Sebastian Gutierrez
Publisher: Apress
Total Pages: 348
Release: 2014-12-12
Genre: Computers
ISBN: 143026599X
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Data Scientists at Work is a collection of interviews with sixteen of the world's most influential and innovative data scientists from across the spectrum of this hot new profession. "Data scientist is the sexiest job in the 21st century," according to the Harvard Business Review. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report. Through incisive in-depth interviews, this book mines the what, how, and why of the practice of data science from the stories, ideas, shop talk, and forecasts of its preeminent practitioners across diverse industries: social network (Yann LeCun, Facebook); professional network (Daniel Tunkelang, LinkedIn); venture capital (Roger Ehrenberg, IA Ventures); enterprise cloud computing and neuroscience (Eric Jonas, formerly Salesforce.com); newspaper and media (Chris Wiggins, The New York Times); streaming television (Caitlin Smallwood, Netflix); music forecast (Victor Hu, Next Big Sound); strategic intelligence (Amy Heineike, Quid); environmental big data (André Karpištšenko, Planet OS); geospatial marketing intelligence (Jonathan Lenaghan, PlaceIQ); advertising (Claudia Perlich, Dstillery); fashion e-commerce (Anna Smith, Rent the Runway); specialty retail (Erin Shellman, Nordstrom); email marketing (John Foreman, MailChimp); predictive sales intelligence (Kira Radinsky, SalesPredict); and humanitarian nonprofit (Jake Porway, DataKind). The book features a stimulating foreword by Google's Director of Research, Peter Norvig. Each of these data scientists shares how he or she tailors the torrent-taming techniques of big data, data visualization, search, and statistics to specific jobs by dint of ingenuity, imagination, patience, and passion. Data Scientists at Work parts the curtain on the interviewees’ earliest data projects, how they became data scientists, their discoveries and surprises in working with data, their thoughts on the past, present, and future of the profession, their experiences of team collaboration within their organizations, and the insights they have gained as they get their hands dirty refining mountains of raw data into objects of commercial, scientific, and educational value for their organizations and clients.

Data Smart

Data Smart
Author: John W. Foreman
Publisher: John Wiley & Sons
Total Pages: 432
Release: 2013-10-31
Genre: Business & Economics
ISBN: 1118839862
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Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Competing in the Age of AI

Competing in the Age of AI
Author: Marco Iansiti
Publisher: Harvard Business Press
Total Pages: 175
Release: 2020-01-07
Genre: Business & Economics
ISBN: 1633697630
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"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.

The YouTube Formula

The YouTube Formula
Author: Derral Eves
Publisher: John Wiley & Sons
Total Pages: 355
Release: 2021-02-24
Genre: Business & Economics
ISBN: 1119716020
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The Wall Street Journal bestseller! Comes with free online companion course Learn the secrets to getting dramatic results on YouTube Derral Eves has generated over 60 billion views on YouTube and helped 24 channels grow to one million subscribers from zero. In The YouTube Formula: How Anyone Can Unlock the Algorithm to Drive Views, Build an Audience, and Grow Revenue, the owner of the largest YouTube how-to channel provides the secrets to getting the results that every YouTube creator and strategist wants. Eves will reveal what readers can't get anywhere else: the inner workings of the YouTube algorithm that's responsible for determining success on the platform, and how creators can use it to their advantage. Full of actionable advice and concrete strategies, this book teaches readers how to: Launch a channel Create life-changing content Drive rapid view and subscriber growth Build a brand and increase engagement Improve searchability Monetize content and audience Replete with case studies and information from successful YouTube creators, The YouTube Formula is perfect for any creator, entrepreneur, social media strategist, and brand manager who hopes to see real commercial results from their work on the platform.

Finish What You Start

Finish What You Start
Author: Peter Hollins
Publisher: PublishDrive
Total Pages: 113
Release: 2019-08-13
Genre: Study Aids
ISBN:
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Practical tactics to grow your willpower, stop procrastination, focus like a laser, and achieve whatever you set your mind to. Following through and finishing what you start- more valuable skills than you realize. They are a combination of traits that enables you to create the life you want - without having to compromise or wait. The alternative is a status quo that you’re stuck in. Is your life a series of unfinished tasks and intentions? That stops now. Finish What You Start is a unique deep dive into the psychology and science of accomplishment, productivity, and getting things done. It takes a thorough look why we are sometimes stuck, and gives detailed, step by step solutions you can start using today. Every phase of finishing and following through is covered, and even productivity pros will be able to learn something new. Above all else, this is a guide to understanding your brain and instincts better for optimal results. Channel massive productivity and mental toughness. Peter Hollins has studied psychology and peak human performance for over a dozen years and is a bestselling author. He has worked with dozens of individuals to unlock their potential and path towards success. His writing draws on his academic, coaching, and research experience. Resist distractions, de-motivation, temptations, laziness, and excuses. •The surprising motivations that push us past obstacles. •How daily rules and a manifesto can help you achieve. •Valuable and insightful mindsets to view productivity from entirely new lights. Seize self-control and finally accomplish your big and small goals. •The science and tactics to beating procrastination easily. •Focus and willpower pitfalls you are probably committing at this very moment. •How to beat distractions, remain focused, stay on task, and get to what matters - consistently. Transform your life through productive habits and avoiding mental traps.

Machine Learning

Machine Learning
Author: Kevin P. Murphy
Publisher: MIT Press
Total Pages: 1102
Release: 2012-08-24
Genre: Computers
ISBN: 0262018020
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A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Plan, Activity, and Intent Recognition

Plan, Activity, and Intent Recognition
Author: Gita Sukthankar
Publisher: Newnes
Total Pages: 423
Release: 2014-03-03
Genre: Computers
ISBN: 012401710X
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Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. Plan, Activity, and Intent Recognition explains the crucial role of these techniques in a wide variety of applications including: personal agent assistants computer and network security opponent modeling in games and simulation systems coordination in robots and software agents web e-commerce and collaborative filtering dialog modeling video surveillance smart homes In this book, follow the history of this research area and witness exciting new developments in the field made possible by improved sensors, increased computational power, and new application areas. Combines basic theory on algorithms for plan/activity recognition along with results from recent workshops and seminars Explains how to interpret and recognize plans and activities from sensor data Provides valuable background knowledge and assembles key concepts into one guide for researchers or students studying these disciplines