• Data science programming all-in-one
  • 點閱:86
  • 作者: by John Paul Mueller and Luca Massaron
  • 出版社:John Wiley & Sons, Inc.
  • 出版年:c2020
  • 集叢名:For dummies
  • ISBN:9781119626114; 9781119626138; 9781119626145
  • 格式:EPUB 流式,PDF,JPG
  • 附註:"Learning made easy"--Cover. Includes index.

Your logical, linear guide to the fundamentals of data science programming
Data science is exploding―in a good way―with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models.
Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time.

Get grounded: the ideal start for new data professionals
What lies ahead: learn about specific areas that data is transforming
Be meaningful: find out how to tell your data story
See clearly: pick up the art of visualization
Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life―and everyone else’s!

John Mueller has produced 114 books and more than 600 articles on topics ranging from functional programming techniques to working with Amazon Web Services (AWS).
Luca Massaron, a Google Developer Expert (GDE),??interprets big data and transforms it into smart data through simple and effective data mining and machine learning techniques.

  • Introduction(第1頁)
    • About This Book(第1頁)
    • Foolish Assumptions(第3頁)
    • Icons Used in This Book(第4頁)
    • Beyond the Book(第4頁)
    • Where to Go from Here(第5頁)
  • Book 1 Defining Data Science(第7頁)
    • Chapter 1 Considering the History and Uses of Data Science(第9頁)
    • Chapter 2 Placing Data Science within the Realm of AI(第29頁)
    • Chapter 3 Creating a Data Science Lab of Your Own(第51頁)
    • Chapter 4 Considering Additional Packages and Libraries You Might Want(第81頁)
    • Chapter 5 Leveraging a Deep Learning Framework(第95頁)
  • Book 2 Interacting with Data Storage(第109頁)
    • Chapter 1 Manipulating Raw Data(第111頁)
    • Chapter 2 Using Functional Programming Techniques(第131頁)
    • Chapter 3 Working with Scalars, Vectors, and Matrices(第171頁)
    • Chapter 4 Accessing Data in Files(第201頁)
    • Chapter 5 Working with a Relational DBMS(第223頁)
    • Chapter 6 Working with a NoSQL DMBS(第237頁)
  • Book 3 Manipulating Data Using Basic Algorithms(第253頁)
    • Chapter 1 Working with Linear Regression(第255頁)
    • Chapter 2 Moving Forward with Logistic Regression(第289頁)
    • Chapter 3 Predicting Outcomes Using Bayes(第309頁)
    • Chapter 4 Learning with K-Nearest Neighbors(第335頁)
  • Book 4 Performing Advanced Data Manipulation(第351頁)
    • Chapter 1 Leveraging Ensembles of Learners(第353頁)
    • Chapter 2 Building Deep Learning Models(第373頁)
    • Chapter 3 Recognizing Images with CNNs(第409頁)
    • Chapter 4 Processing Text and Other Sequences(第453頁)
  • Book 5 Performing Data-Related Tasks(第491頁)
    • Chapter 1 Making Recommendations(第493頁)
    • Chapter 2 Performing Complex Classifications(第509頁)
    • Chapter 3 Identifying Objects(第525頁)
    • Chapter 4 Analyzing Music and Video(第543頁)
    • Chapter 5 Considering Other Task Types(第559頁)
    • Chapter 6 Developing Impressive Charts and Plots(第579頁)
  • Book 6 Diagnosing and Fixing Errors(第619頁)
    • Chapter 1 Locating Errors in Your Data(第621頁)
    • Chapter 2 Considering Outrageous Outcomes(第643頁)
    • Chapter 3 Dealing with Model Overfitting and Underfitting(第663頁)
    • Chapter 4 Obtaining the Correct Output Presentation(第689頁)
    • Chapter 5 Developing Consistent Strategies(第707頁)
  • Index(第721頁)
紙本書 NT$ 1280
NT$ 1280

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