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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
| Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas |
| Autore | Crimi Alessandro |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.) |
| Disciplina | 006.37 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Artificial intelligence Computer engineering Computer networks Application software Computer Vision Artificial Intelligence Computer Engineering and Networks Computer and Information Systems Applications |
| Soggetto non controllato |
artificial intelligence
bioinformatics computer science computer systems computer vision education image analysis image processing image segmentation learning machine learning medical images neural networks pattern recognition segmentation methods software design software engineering software quality validation verification and validation |
| ISBN | 3-031-08999-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Supervoxel Merging towards Brain Tumor Segmentation -- Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma -- Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks -- Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task -- Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation -- BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance -- Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism -- Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans -- MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation -- Unsupervised Multimodal -- HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation -- Multimodal Brain Tumor Segmentation Algorithm -- Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images -- Multi-plane UNet++ Ensemble for Glioblastoma Segmentation -- Multimodal Brain Tumor Segmentation using Modified UNet Architecture -- A video data based transfer learning approach for classification of MGMT status in brain tumor MR images -- Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021 -- 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function -- 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge -- Cascaded training pipeline for 3D brain tumor segmentation -- nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation -- Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining -- Automatic segmentation of brain tumor using 3D convolutional neural networks -- Hierarchical and Global Modality Interaction for Brain Tumor Segmentation -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- Brain Tumor Segmentation using UNet-Context Encoding Network -- Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI. |
| Record Nr. | UNISA-996483157303316 |
Crimi Alessandro
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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C++ Programming Fundamentals
| C++ Programming Fundamentals |
| Autore | Malhotra D |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York : , : Mercury Learning & Information, , 2022 |
| Descrizione fisica | 1 online resource (289 pages) |
| Disciplina | 005.133 |
| Altri autori (Persone) | MalhotraN |
| Soggetto topico | COMPUTERS / Programming Languages / C++ |
| Soggetto non controllato |
AI
arrays computer science developers embedded systems file handling game design pointers polymorphism programming video game |
| ISBN |
1-68392-974-8
1-68392-975-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title -- Copyright -- Contents -- Preface -- Acknowledgments -- Chapter 1 C++ and Beyond -- Introduction -- 1.1 The Origin of C++ -- 1.2 Why Use C++? -- 1.3 Various Programming Paradigms -- 1.3.1 Structural Programming -- 1.3.2 Procedural Programming -- 1.3.3 Object Oriented Programming -- 1.4 C++ Basics -- 1.4.1 Variables -- 1.4.2 Data Types -- 1.4.3 Data Modifiers -- 1.t C++ Execution Flow -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Application -- References -- Books -- Websites -- Chapter 2 Basic Play in C++ -- 2.1 Literals, Constants, and Qualifiers -- 2.2 Stream-Based IO -- 2.3 Comments -- 2.4 Operators and Types -- 2.4.1 Types of Operators in C++ -- 2.5 Type Conversion -- 2.6 Keywords -- 2.7 Loops in C++ -- 2.9 Control Statements -- 2.9 Defining Functions -- 2.9.1 Why Use Functions? -- 2.10 C vs. C++ -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Questions -- References -- Books -- Websites -- Chapter 3 Arrays and Strings -- 3.1 What is an Array? -- 3.1.1 Ways to Declare Arrays -- 3.1.2 Ways to Access Array Members -- 3.1.3 Traversing a 1D Array -- 3.2 Operations on an Array -- 3.2.1 Passing an Array to Functions -- 3.2.2 Finding the Length -- 3.2.3 Enum in C++ -- 3.2.4 Searching -- 3.3 Multi-Dimensional Array -- 3.4 Strings -- 3.5 String Functions -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Questions -- References -- Books -- Websites -- Chapter 4 Pointers in C++ -- 4.1 Introduction -- 4.2 Pointers: Declaration and Initialization -- 4.3 Casting and Passing Pointers -- 4.3.1 Typecasting -- 4.3.2 Passing -- 4.4 Using Pointers with Arrays -- 4.5 Pointer Use -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 5 Classes in C++ -- 5.1 Class Making.
5.2 Constructors and Destructors -- 5.3 The This Pointer -- 5.4 Class Methods -- 5.5 The static Keyword -- 5.6 Memory Management and Garbage Collection in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 6 Inheritance -- 6.1 Introduction -- 6.2 Inheritance -- 6.2.1 Access Specifiers -- 6.2.2 Inheritance Modes -- 6.3 Types of Inheritance -- 6.4 Constructor Calling -- 6.5 Implementing Inheritance -- Summary -- Exercises -- Theory Questions -- Practial Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 7 Polymorphism -- 7.1 Introduction -- 7.2 Dynamic vs. Static Binding -- 7.3 Interface and Implementation -- 7.4 Function Overriding and Overloading -- 7.5 Friend and Generic Functions -- 7.5.1 Friend Functions -- 7.5.2 Generic Functions -- 7.6 Namespaces -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 8 Operator Overloading -- 8.1 Basics -- 8.2 How to Overload an Operator? -- 8.3 Overloading Unary Operators -- 8.4 Overloading Binary Operators -- 8.5 Overloading by Friend Function -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 9 Structure and Union -- 9.1 Structure: Declaration and Definition -- 9.2 Accessing a Structure -- 9.3 Union -- 9.4 Differences Between Structure and Union -- 9.5 Enum in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 10 Exception Handling -- 10.1 Errors and Exceptions -- 10.2 Exception Handling -- 10.3 Various Exceptions -- 10.4 Custom Exceptions in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 11 File Handling. 11.1 Files and Streams -- 11.2 File Operations -- 11.3 Random Access and Object Serialization -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Index. |
| Record Nr. | UNINA-9910838375803321 |
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Malhotra D
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| New York : , : Mercury Learning & Information, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel
| Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel |
| Autore | Shoham Sharon |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (560 pages) : illustrations (black and white) |
| Altri autori (Persone) | VizelYakir |
| Collana | Lecture notes in computer science |
| Soggetto topico | Computer software - Verification |
| Soggetto non controllato |
architecting
architecture verification and validation artificial intelligence computer programming computer science computer systems databases distributed computer systems embedded systems engineering formal languages formal logic linguistics mathematics model checking software architecture software design software engineering software quality theoretical computer science |
| ISBN | 3-031-13188-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996485664103316 |
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Shoham Sharon
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel
| Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel |
| Autore | Shoham Sharon |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (563 pages) : illustrations (black and white) |
| Disciplina | 005.14 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Computer software - Verification |
| Soggetto non controllato |
architecting
architecture verification and validation artificial intelligence computer programming computer science computer systems distributed computer systems distributed systems embedded systems formal logic mathematics model checking programming languages software architecture software design software engineering software quality theoretical computer science verification verification and validation |
| ISBN | 3-031-13185-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996485664203316 |
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Shoham Sharon
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Computer Science and Engineering Education for Pre-collegiate Students and Teachers / Andrea Burrows
| Computer Science and Engineering Education for Pre-collegiate Students and Teachers / Andrea Burrows |
| Autore | Burrows Andrea |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (142 p.) |
| Soggetto topico | Education |
| Soggetto non controllato |
secondary science
STEM outreach mathematics (STEM) education environmental radioactivity learner analysis coaching learner-centered pedagogy preservice teacher beliefs computer science education laboratory activity science education challenge-based learning engineering K–12 teacher literature review pre-collegiate teacher scintillator detector computing outreach science computer science application pre-college engineering activities K-12 teachers engineering design process ?-ray spectroscopy student engagement in-situ measurements conceptual assessment items engineering education Web-GIS platform K–12 computer science engineering outreach online professional development training pre-college STEM activities Android app students’ alternative conceptions technology inquiry-based science and technology computer science integration assessment tool perceptions pre-college computing activities nuclear engineering experiment conceptual change NGSS physics education engineering design technology |
| ISBN |
9783038979418
3038979414 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346689903321 |
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Burrows Andrea
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Science for IoT Engineers : A Systems Analytics Approach
| Data Science for IoT Engineers : A Systems Analytics Approach |
| Autore | Madhavan P. G |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2021 |
| Descrizione fisica | 1 online resource (170 pages) |
| Disciplina | 006.312024004678 |
| Soggetto topico | COMPUTERS / Desktop Applications / Presentation Software |
| Soggetto non controllato |
IOT
MATLAB computer science data analytics engineering mathematics physics |
| ISBN |
1-68392-640-4
1-68392-641-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index |
| Record Nr. | UNINA-9910795555703321 |
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Madhavan P. G
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| Bloomfield : , : Mercury Learning & Information, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Science for IoT Engineers : A Systems Analytics Approach
| Data Science for IoT Engineers : A Systems Analytics Approach |
| Autore | Madhavan P. G |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2021 |
| Descrizione fisica | 1 online resource (170 pages) |
| Disciplina | 006.312024004678 |
| Soggetto topico | COMPUTERS / Desktop Applications / Presentation Software |
| Soggetto non controllato |
IOT
MATLAB computer science data analytics engineering mathematics physics |
| ISBN |
1-68392-640-4
1-68392-641-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index |
| Record Nr. | UNINA-9910810050903321 |
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Madhavan P. G
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| Bloomfield : , : Mercury Learning & Information, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data sciences : from first-order logic to the web / / Serge Abiteboul, translator: Liz Libbrecht
| Data sciences : from first-order logic to the web / / Serge Abiteboul, translator: Liz Libbrecht |
| Autore | Abiteboul Serge |
| Pubbl/distr/stampa | Collège de France, 2012 |
| Descrizione fisica | 1 online resource (110 pages) : illustrations |
| Collana | Leçons inaugurales du Collège de France |
| Soggetto topico |
Computer science
Data science Algorithm Engineering & Applied Sciences Computer Science |
| Soggetto non controllato |
inaugural lecture
computer science data science Web knowledge algorithm |
| ISBN | 9782722601796 (ebook) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910137592103321 |
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Abiteboul Serge
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| Collège de France, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Structures in Java
| Data Structures in Java |
| Autore | Campesato Oswald |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2023 |
| Descrizione fisica | 1 online resource (248 pages) |
| Disciplina | 005.133 |
| Soggetto topico |
Data structures (Computer science)
Java (Computer program language) COMPUTERS / Programming Languages / Java |
| Soggetto non controllato |
XOR
arrays business combinatorics computer science data analysis queues recursion stacks strings |
| ISBN |
1-68392-953-5
1-68392-954-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Dedication -- Contents -- Preface -- Chapter 1: Introduction to Java -- A Very Brief Introduction to Java -- Downloading a Java Release (Short Version) -- Selecting a Version of Java (Detailed Version) -- Java 8 and Java 11 -- Java Version Numbers -- JRE Versus a JDK -- Java Distributions -- Java IDEs -- Data Types, Operators, and Their Precedence -- Java Comments -- Java Operators -- Creating and Compiling Java Classes -- "Hello World" and Working With Numbers -- The Java String Class -- Java Strings With Metacharacters -- The Java New Operator -- Equality of Strings -- Comparing Strings -- Searching for a Substring in Java -- Useful String Methods in Java -- Parsing Strings in Java -- Conditional Logic in Java -- Determining Leap Years -- Finding the Divisors of a Number -- Checking for Palindromes -- Working With Arrays of Strings -- Working With the StringBuilder Class -- Static Methods in Java -- Other Static Types in Java -- Summary -- Chapter 2: Recursion and Combinatorics -- What Is Recursion? -- Arithmetic Series -- Calculating Arithmetic Series (Iterative) -- Calculating Arithmetic Series (Recursive) -- Calculating Partial Arithmetic Series -- Geometric Series -- Calculating a Geometric Series (Iterative) -- Calculating Geometric Series (Recursive) -- Factorial Values -- Calculating Factorial Values (Iterative) -- Calculating Factorial Values (Recursive) -- Calculating Factorial Values (Tail Recursion) -- Fibonacci Numbers -- Calculating Fibonacci Numbers (Recursive) -- Calculating Fibonacci Numbers (Iterative) -- Task: Reverse a String via Recursion -- Task: Check for Balanced Parentheses -- Task: Calculate the Number of Digits -- Task: Determine if a Positive Integer is Prime -- Task: Find the Prime Divisors of a Positive Integer -- Task: Goldbach's Conjecture.
Task: Calculate the GCD (Greatest Common Divisor) -- Task: Calculate the LCM (Lowest Common Multiple) -- What Is Combinatorics? -- Working With Permutations -- Working With Combinations -- The Number of Subsets of a Finite Set -- Task: Subsets Containing a Value Larger Than k -- Summary -- Chapter 3: Strings and Arrays -- Time and Space Complexity -- Task: Maximum and Minimum Powers of an Integer -- Task: Binary Substrings of a Number -- Task: Common Substring of Two Binary Numbers -- Task: Multiply and Divide via Recursion -- Task: Sum of Prime and Composite Numbers -- Task: Count Word Frequencies -- Task: Check if a String Contains Unique Characters -- Task: Insert Characters in a String -- Task: String Permutations -- Task: Check for Palindromes -- Task: Check for Longest Palindrome -- Working With Sequences of Strings -- The Maximum Length of a Repeated Character in a String -- Find a Given Sequence of Characters in a String -- Task: Longest Sequences of Substrings -- The Longest Sequence of Unique Characters -- The Longest Repeated Substring -- Working With 1D Arrays -- Rotate an Array -- Task: Invert Adjacent Array Elements -- Task: Shift Nonzero Elements Leftward -- Task: Sort Array In-Place in O(n) Without a Sort Function -- Task: Generate 0 That Is Three Times More Likely Than a 1 -- Task: Invert Bits in Even and Odd Positions -- Task: Check for Adjacent Set Bits in a Binary Number -- Task: Count Bits in a Range of Numbers -- Task: Find the Right-Most Set Bit in a Number -- Task: The Number of Operations to Make All Characters Equal -- Task: Compute XOR without XOR for Two Binary Numbers -- Task: Swap Adjacent Bits in Two Binary Numbers -- Working With 2D Arrays -- The Transpose of a Matrix -- Summary -- Chapter 4: Search and Sort Algorithms -- Search Algorithms -- Linear Search -- Binary Search Walk-Through. Binary Search (Iterative Solution) -- Binary Search (Recursive Solution) -- Well-Known Sorting Algorithms -- Bubble Sort -- Find Anagrams in a List of Words -- Selection Sort -- Insertion Sort -- Comparison of Sort Algorithms -- Merge Sort -- Merge Sort With a Third Array -- Merge Sort Without a Third Array -- Merge Sort: Shift Elements From End of Lists -- How Does Quick Sort Work? -- Quick Sort Code Sample -- Shell Sort -- Task: Sorted Arrays and the Sum of Two Numbers -- Summary -- Chapter 5: Linked Lists (1) -- Types of Data Structures -- Linear Data Structures -- Nonlinear Data Structures -- Data Structures and Operations -- Operations on Data Structures -- What Are Singly Linked Lists? -- Tradeoffs for Linked Lists -- Singly Linked Lists: Create and Append Operations -- A Node Class for Singly Linked Lists -- Java Code for Appending a Node -- Finding a Node in a Linked List -- Appending a Node in a Linked List -- Finding a Node in a Linked List (Method 2) -- Singly Linked Lists: Update and Delete Operations -- Updating a Node in a Singly Linked List -- Java Code to Update a Node -- Deleting a Node in a Linked List -- Java Code for Deleting a Node -- Java Code for a Circular Linked List -- Java Code for Updating a Circular Linked List -- Working With Doubly Linked Lists (DLL) -- A Node Class for Doubly Linked Lists -- Appending a Node in a Doubly Linked List -- Java Code for Appending a Node -- Java Code for Inserting a New Root Node -- Java Code for Inserting an Intermediate Node -- Traversing the Nodes in a Doubly Linked List -- Updating a Node in a Doubly Linked List -- Java Code to Update a Node -- Deleting a Node in a Doubly Linked List -- Java Code to Delete a Node -- Summary -- Chapter 6: Linked Lists (2) -- Task: Adding Numbers in a Linked List (1) -- Task: Adding Numbers in a Linked List (2) -- Task: Adding Numbers in a Linked List (3). Task: Display the First k Nodes -- Task: Display the Last k Nodes -- Reverse a Singly Linked List via Recursion -- Task: Remove Duplicates -- Task: Concatenate Two Lists -- Task: Merge Two Ordered Linked Lists -- Task: Split an Ordered List Into Two Lists -- Task: Remove a Given Node from a List -- Task: Find the Middle Element in a List -- Task: Reverse a Linked List -- Task: Check for Palindrome in a Linked List -- Summary -- Chapter 7: Queues and Stacks -- What Is a Queue? -- Types of Queues -- Creating a Queue Using an Array List -- Creating a Queue Using an Array List -- Other Types of Queues -- What Is a Stack? -- Use Cases for Stacks -- Operations With Stacks -- Working With Stacks -- Task: Reverse and Print Stack Values -- Task: Display the Min and Max Stack Values (1) -- Task: Reverse a String Using a Stack -- Task: Find Stack Palindromes -- Task: Balanced Parentheses -- Task: Tokenize Arithmetic Expressions -- Task: Classify Tokens in Arithmetic Expressions -- Infix, Prefix, and Postfix Notations -- Summary -- Index. |
| Record Nr. | UNINA-9910861061603321 |
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Campesato Oswald
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| Bloomfield : , : Mercury Learning & Information, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Dealing with Data Pocket Primer
| Dealing with Data Pocket Primer |
| Autore | Campesato Oswald |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2022 |
| Descrizione fisica | 1 online resource (246 pages) |
| Disciplina | 001.42 |
| Collana | Computing |
| Soggetto topico |
Quantitative research - Reliability
Quantitative research - Data processing |
| Soggetto non controllato |
NLP
Pandas RDBMS SQL computer science data analytics data cleaning data visualization programming python statistics |
| ISBN |
1-5231-4740-7
1-68392-818-0 1-68392-819-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- Preface -- Chapter 1: Introduction to Probability and Statistics -- Chapter 2: Working with Data -- Chapter 3: Introduction to Pandas -- Chapter 4: Introduction to RDBMS and SQL -- Chapter 5: Working with SQL and MySQL -- Chapter 6: NLP and Data Cleaning -- Chapter 7: Data Visualization -- Index |
| Record Nr. | UNINA-9910795724303321 |
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Campesato Oswald
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| Bloomfield : , : Mercury Learning & Information, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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