자료유형 | E-Book |
---|---|
개인저자 | Saleh, Hyatt, author. |
서명/저자사항 | The machine learning workshop. |
판사항 | Second edition. |
발행사항 | Birmingham, UK : Packt Publishing, 2020. |
형태사항 | 1 online resource (1 volume) : illustrations |
소장본 주기 | OCLC control number change |
ISBN | 9781838985462 1838985468 |
내용주기 | Cover -- FM -- Copyright -- Table of Contents -- Preface -- Chapter 1: Introduction to Scikit-Learn -- Introduction -- Introduction to Machine Learning -- Applications of ML -- Choosing the Right ML Algorithm -- Scikit-Learn -- Advantages of Scikit-Learn -- Disadvantages of Scikit-Learn -- Other Frameworks -- Data Representation -- Tables of Data -- Features and Target Matrices -- Exercise 1.01: Loading a Sample Dataset and Creating the Features and Target Matrices -- Activity 1.01: Selecting a Target Feature and Creating a Target Matrix -- Data Preprocessing -- Messy Data -- Missing Values Outliers -- Exercise 1.02: Dealing with Messy Data -- Dealing with Categorical Features -- Feature Engineering -- Exercise 1.03: Applying Feature Engineering to Text Data -- Rescaling Data -- Exercise 1.04: Normalizing and Standardizing Data -- Activity 1.02: Pre-processing an Entire Dataset -- Scikit-Learn API -- How Does It Work? -- Estimator -- Predictor -- Transformer -- Supervised and Unsupervised Learning -- Supervised Learning -- Unsupervised Learning -- Summary -- Chapter 2: Unsupervised Learning -- Real-Life Applications -- Introduction -- Clustering -- Clustering Types Applications of Clustering -- Exploring a Dataset -- Wholesale Customers Dataset -- Understanding the Dataset -- Data Visualization -- Loading the Dataset Using pandas -- Visualization Tools -- Exercise 2.01: Plotting a Histogram of One Feature from the Circles Dataset -- Activity 2.01: Using Data Visualization to Aid the Pre-processing Process -- k-means Algorithm -- Understanding the Algorithm -- Initialization Methods -- Choosing the Number of Clusters -- Exercise 2.02: Importing and Training the k-means Algorithm over a Dataset -- Activity 2.02: Applying the k-means Algorithm to a Dataset Mean-Shift Algorithm -- Understanding the Algorithm -- Exercise 2.03: Importing and Training the Mean-Shift Algorithm over a Dataset -- Activity 2.03: Applying the Mean-Shift Algorithm to a Dataset -- DBSCAN Algorithm -- Understanding the Algorithm -- Exercise 2.04: Importing and Training the DBSCAN Algorithm over a Dataset -- Activity 2.04: Applying the DBSCAN Algorithm to the Dataset -- Evaluating the Performance of Clusters -- Available Metrics in Scikit-Learn -- Exercise 2.05: Evaluating the Silhouette Coefficient Score and Calinski-Harabasz Index Activity 2.05: Measuring and Comparing the Performance of the Algorithms -- Summary -- Chapter 3: Supervised Learning -- Key Steps -- Introduction -- Supervised Learning Tasks -- Model Validation and Testing -- Data Partitioning -- Split Ratio -- Exercise 3.01: Performing a Data Partition on a Sample Dataset -- Cross-Validation -- Exercise 3.02: Using Cross-Validation to Partition the Train Set into a Training and a Validation Set -- Activity 3.01: Data Partitioning on a Handwritten Digit Dataset -- Evaluation Metrics -- Evaluation Metrics for Classification Tasks -- Confusion Matrix -- Accuracy |
요약 | With expert guidance and real-world examples, The Machine Learning Workshop gets you up and running with programming machine learning algorithms. By showing you how to leverage scikit-learn's flexibility, it teaches you all the skills you need to use machine learning to solve real-world problems. |
일반주제명 | Machine learning. Neural networks (Computer science) Artificial intelligence. Machine learning Python (Computer program language) |
언어 | 영어 |
기타형태 저록 | Print version:Saleh, HyattThe the Machine Learning Workshop : Get Ready to Develop Your Own High-Performance Machine Learning Algorithms with Scikit-learn, 2nd EditionBirmingham : Packt Publishing, Limited,c2020 |
대출바로가기 | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2532421 |
인쇄
No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
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1 | WE00018788 | 006.31 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |