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Univ. Federico II (50)

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Advanced Analytics with Power BI and Excel : Learn Powerful Visualization and Data Analysis Techniques Using Microsoft BI Tools along with Python and R

Dejan Sarka Jernej Rihar

Delhi : , : Orange Education PVT Ltd, , 2023

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Lo trovi qui: Univ. Federico II

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Advanced Data Analytics with AWS : Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources (English Edition)

Conley Joseph

Delhi : , : Orange Education PVT Ltd, , 2024

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Lo trovi qui: Univ. Federico II

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Building Scalable Web Apps with Node. js and Express : Design and Develop a Robust, Scalable, High-Performance Web Application Using Node. js, Express. js, TypeScript, and Redis (English Edition)

Yamini Panchal Ravi Kumar Gupta

Delhi : , : Orange Education PVT Ltd, , 2024

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Cloud Security Handbook for Architects

Mishra Ashish

Delhi : , : Orange Education PVT Ltd, , 2023

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Graph Data Science with Python and Neo4j : Hands-On Projects on Python and Neo4j Integration for Data Visualization and Analysis Using Graph Data Science for Building Enterprise Strategies (English Edition)

Eastridge Timothy

Delhi : , : Orange Education PVT Ltd, , 2024

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Mastering ChatGPT and Google Colab for Machine Learning : Automate AI Workflows and Fast-Track Your Machine Learning Tasks with the Power of ChatGPT, Google Colab, and Python (English Edition)

Moscato Rosario

Delhi : , : Orange Education PVT Ltd, , 2024

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Mastering Data Engineering and Analytics with Databricks : A Hands-On Guide to Build Scalable Pipelines Using Databricks, Delta Lake, and MLflow (English Edition)

Kumar Manoj

Delhi : , : Orange Education PVT Ltd, , 2024

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Mastering IoT for Industrial Environments : Unlock the IoT Landscape for Industrial Environments with Industry 4. 0, Covering Architecture, Protocols Like MQTT, and Advancements with ESP-IDF (English Edition)

Sharma Shrey

Delhi : , : Orange Education PVT Ltd, , 2024

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Mastering OpenCV with Python

Vaishya Ayush

Delhi : , : Orange Education PVT Ltd, , 2023

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Microservices with Spring Boot and Spring Cloud : Develop Modern, Resilient, Scalable and Highly Available Apps Using Microservices with Java, Spring Boot 3. 0 and Spring Cloud

Jog Tejaswini

Delhi : , : Orange Education PVT Ltd, , 2023

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Orange Education PVT Ltd (50)

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2024 (31)
2023 (20)

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Machine learning (7)
Cloud computing (5)
Computer security (3)
Microsoft Azure (Computing platform) (3)
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Autore	Dejan Sarka Jernej Rihar
Edizione	[1st ed.]
Pubbl/distr/stampa	Delhi : , : Orange Education PVT Ltd, , 2023
Descrizione fisica	1 online resource (398 pages)
Soggetto topico	Information visualization
ISBN	9789391246709
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910915698803321

Autore	Conley Joseph
Edizione	[1st ed.]
Pubbl/distr/stampa	Delhi : , : Orange Education PVT Ltd, , 2024
Descrizione fisica	1 online resource (182 pages)
Soggetto topico	Cloud computing
ISBN	9788197081897 8197081891
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Altri titoli varianti	Advanced data analytics with Amazon Web Services
Record Nr.	UNINA-9910985666103321

Autore	Yamini Panchal Ravi Kumar Gupta
Edizione	[1st ed.]
Pubbl/distr/stampa	Delhi : , : Orange Education PVT Ltd, , 2024
Descrizione fisica	1 online resource (207 pages)
Soggetto topico	Web applications TypeScript (Computer program language)
ISBN	9788197223815
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Cover Page -- Title Page -- Copyright Page -- About the Authors -- About the Technical Reviewer -- Acknowledgements -- Preface -- Errata -- Table of Contents -- 1. Introduction to Node.js -- Introduction -- Structure -- Defining Node.Js -- Applications of Node.js -- Single-Page Applications -- Real-time Applications -- IoT Devices Applications -- Data Streaming Application -- Pros of Node.js -- Cons of Node.js -- Installing Node.js -- Installing Node For Linux/Ubuntu -- Installing Node.js for Windows -- Installing Node.js for mac -- Event-Driven Mechanism -- Example of Event Programming -- Example of Synchronous Code -- Example of Asynchronous code -- Types of Node.js Architectures -- Monolithic Architecture
Record Nr.	UNINA-9911009249103321

Autore	Mishra Ashish
Edizione	[1st ed.]
Pubbl/distr/stampa	Delhi : , : Orange Education PVT Ltd, , 2023
Descrizione fisica	1 online resource (291 pages)
ISBN	9789395968997
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Intro -- Cover Page -- Title Page -- Copyright Page -- Foreword -- Dedication Page -- About the Author -- Technical Reviewers -- Acknowledgements -- Preface -- Errata -- Table of Contents -- SECTION I: Overview and Need to Transform to Cloud Landscape -- 1. Evolution of Cloud Computing and its Impact on Security -- Introduction -- Structure -- Evolution of cloud -- Cloud computing journey -- Cloud computing overview -- Characteristics of cloud computing -- Cloud types -- Cloud computing service model -- Cloud computing trends -- Recognizing the development of cloud -- Justifications for using the cloud -- Analyzing the risk of cloud services -- Inherent risk -- Techniques to reduce the inherent risk -- Cloud computing privacy concerns -- Assessing your organization's cloud maturity -- Analyzing the development of cloud risk -- Shadow IT and its rise -- Understanding the shared responsibility paradigm -- Key considerations for the upliftment of cloud security -- Risk analysis -- Controls on user access -- Automation -- Continual monitoring -- Conclusion -- Reference -- 2. Understanding the Core Principles of Cloud Security and its Importance -- Introduction -- Structure -- Principles and concept understanding -- Most restrictive -- Defense in Depth -- Threat actors as well as trust limits -- Segregation of duties -- Fail-safe -- Economy of mechanism -- Complete mediation -- Open design -- Least common mechanism -- Weakest chain -- Making use of the current landscape -- Architectural considerations -- Basic concerns -- Compliance -- Security control -- Controls -- Additional controls -- Information classification -- Objectives for information classification -- Benefits of information classification -- Concepts behind information classification -- Classification criteria -- Procedures for classifying information. Security awareness, training, and education -- Security awareness -- Instruction and learning -- PKI and encryption key management -- Digital certificate -- Identity and access management -- Identity management -- Passwords -- Implementing identity management solution -- Access controls -- Controls -- Controlling access types -- Mandatory access control -- Discretionary access control -- Non-discretionary access control -- Single Sign-On (SSO) -- Strategy to adopt cloud security -- Enabling secure cloud migrations with a cross-platform, integrated segmentation strategy -- Avoiding problems associated with complex, segregated, and bloated legacy data -- Examining the danger posed by the extended attack surface of the cloud -- Best practices on cloud security -- Recognizing the shared responsibility model -- Asking detailed security questions to your cloud provider -- Installing Identity and Access Management (IAM) software -- Your staff should receive training -- Creating and enforcing cloud security guidelines -- Protecting your endpoints -- Securing data while it is moving and at rest -- Utilizing technology for intrusion detection and prevention -- Audits and penetration testing should be performed -- Conclusion -- References -- 3. Cloud Landscape Assessment and Choosing a Solution for Your Enterprise -- Introduction -- Structure -- Defining organization cloud security roles and responsibilities -- Deep-dive into the Shared Responsibility Model -- Cloud Service Provider (CSP) responsibilities -- Customer responsibilities -- Core cloud team roles and responsibilities -- Understanding team structures -- Managing risk in the cloud -- Risk Management Framework (RMF) -- Cloud Service Provider (CSP) risk management process -- Customer's risk management process for cloud landscape -- Monitoring and managing cloud risk. An approach towards cloud security assessment -- Basic principles for cloud security assessment -- Need to adopt cloud security assessment -- Benefits of adopting cloud security assessment -- Ideas to keep in mind before beginning your assessment -- Executing cloud security assessment -- Architecture overview -- Internal versus internet-based enterprise assessments -- Guidelines -- Account management and user authentication -- Vulnerability assessments for network and systems -- External alone, internal only, or both -- Server and workstation compliance assessment -- Network and security system compliance assessment -- Testing the security of web applications -- Hypervisor layer assessment -- Reporting and sharing the data that follows -- Selecting the right cloud service provider (CSP) -- Time to choose the right cloud service provider -- Cloud security -- Standards and accreditations -- Roadmap for technologies and services -- Security and data governance -- Dependencies and partnerships for services -- SLAs, commercials, and contracts -- Performance and dependability -- Provider lock-in, exit strategy, and migration support -- Conclusion -- References and useful information -- SECTION II: Building Blocks of Cloud Security Framework and Adoption Path -- 4. Cloud Security Architecture and Implementation Framework -- Introduction -- Structure -- Cloud security architecture overview -- Key elements and responsibilities of cloud architecture -- Shared responsibilities in cloud security architecture -- Infrastructure as a Service (IaaS) -- Software as a Service (SaaS) -- Platform as a Service (PaaS) -- Architectural type for cloud security -- Cloud security architecture building blocks -- Evolution of cloud security architecture -- Responsibilities of cloud security architecture -- Public cloud versus private cloud -- CSP versus customer. Adoption of cloud security architecture on various service models -- Software as a Service (SaaS) -- Infrastructure as a Service (IaaS) -- Platform as a Service (PaaS) -- Cloud security framework -- System design -- Operational excellence -- Security, compliance, and privacy -- Reputation -- Cost management -- Performance management -- Adopting cloud security -- Five phases of adoption -- The foundational layer -- The perimeter layer -- Data protection -- Visibility -- Cloud solution -- Cloud security principles -- Autonomic security -- Autonomic system -- Autonomic protection -- Autonomic healing -- Evaluating the cloud security maturity model -- Cloud migration -- Software development for the cloud -- Need to shift software to cloud -- Strategy for cloud migration -- Real-time challenges while migrating to cloud -- Benefits of cloud migration -- Approaches to cloud migration -- Scenarios for cloud migration -- Common cloud services centralization -- Need to centralize common services -- Consumer PaaS -- Resources and services for development -- Public facing services -- Security services -- Human impact -- Spending money on people -- Support staff -- Microservices and container security -- Microservices-based architecture -- Securing the microservices architecture -- Adopting security while designing the solution -- Verifying dependencies -- Adopting HTTPS for everything -- Making use of identity and access tokens -- Securing secrets via encryption -- Knowing how to secure your cloud and cluster -- Covering all of your security bases -- Conclusion -- References and useful information -- Questions -- 5. Native Cloud Security Controls and Building Blocks -- Introduction -- Structure -- Asset management and protection -- Classification and identification of data -- Classification level for data -- Relevant regulatory or industry requirements. Cloud-based data asset management -- Cloud resource tags -- Data protection in the cloud -- Tokenization -- Encryption -- Key management -- Encryption on both the client and server sides -- Cryptographic erasure -- Enabling encryption to protect against different attacks -- Tagging cloud assets -- IAM on cloud -- Enterprise-to-Employee (B2B) and Enterprise-to-Consumer (B2C) -- Multi-Factor Authentication (MFA) -- API keys and passwords -- Shared credentials -- Single Sign-On (SSO) -- SAML and OIDC -- SSO with legacy applications -- Vulnerability management -- Differences in traditional IT -- Components that are at risk -- Data access layer -- Application layer -- Middleware -- Operating system -- Virtual infrastructure -- Physical infrastructure -- Vulnerability scanners for networks -- Cloud Service Provider (CSP) security management tools -- Container scanner -- Dynamic Application Security Testing (DAST) -- Static Application Security Testing (SAST) -- Software Composition Analysis Scanner (SCA) -- Interactive Application Scanning Test (IAST) -- Runtime Application Self-Protection (RASP) -- Code reviews -- A few tools for vulnerability management -- Network security -- Concepts and definitions -- Whitelists and blacklists -- DMZ -- Proxies -- SDN -- Feature of the network virtualization -- Encapsulation and overlay networks -- Virtual Private Cloud (VPC) -- Network Address Translation (NAT) -- Adoption path of network security components -- Encryption in motion -- Segmenting the network with firewalls -- Perimeter controls -- Internal segmentation -- Security groups -- Network segmentation and firewall policies for container -- Administrative access -- Jump servers (or bastion hosts) -- Virtual Private Network (VPN) -- Site-to-site communications -- Client-to-site communications -- Web Application Firewall (WAF) -- DDoS protection. Intrusion Detection System (IDS) and Intrusion Prevention System (IPS).
Record Nr.	UNINA-9910860868003321

Autore	Eastridge Timothy
Edizione	[1st ed.]
Pubbl/distr/stampa	Delhi : , : Orange Education PVT Ltd, , 2024
Descrizione fisica	1 online resource (118 pages)
Soggetto topico	Graph databases Machine learning
ISBN	9788197081965 8197081964
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Cover Page -- Title Page -- Copyright Page -- Dedication Page -- About the Author -- About the Technical Reviewer -- Acknowledgements -- Preface -- A Note from the Author -- Errata -- Table of Contents -- 1. Introduction to Graph Data Science -- Introduction -- Structure -- Data Science and Machine Learning -- Defining Graph -- The importance of Graph Structures -- Introducing Neo4j Graph Database -- Knowledge Graphs -- Introducing Python Programming Language -- Conclusion -- Multiple Choice Questions -- Answers -- 2. Getting Started with Python and Neo4j -- Introduction -- Structure -- Installing and Setting Up Python and Neo4j -- Installing Python -- Executing Python Code Using Common Libraries -- Incorporating New Libraries Using Conda
Record Nr.	UNINA-9910985653903321

Autore	Vaishya Ayush
Edizione	[1st ed.]
Pubbl/distr/stampa	Delhi : , : Orange Education PVT Ltd, , 2023
Descrizione fisica	1 online resource (239 pages)
Soggetto topico	Computer vision Image processing
ISBN	9789390475797 9390475791
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Intro -- Cover Page -- Title Page -- Copyright Page -- Dedication Page -- About the Author -- About the Technical Reviewer -- Acknowledgements -- Preface -- Errata -- Table of Contents -- 1. Introduction to Computer Vision -- Introduction -- Structure -- Introduction to Computer Vision -- Applications of Computer Vision -- Python -- OpenCV. -- Brief history of OpenCV -- OpenCV 4.7 -- Supporting Libraries -- NumPy -- Matplotlib -- SciPy -- Scikit-Learn -- Scikit-Image -- Mahotas -- TensorFlow -- Keras -- Dlib -- Environment Setup -- Installing Python -- Installing Python on Windows -- Installing Python on Ubuntu and Mac -- Package Manager -- Installing libraries -- Installing Mahotas -- Installing OpenCV -- Verifying our installation -- IDE -- Documentation -- Conclusion -- Test Your Understanding -- 2. Getting Started with Images -- Structure -- Introduction to images and pixels -- Loading and displaying images -- Imread() -- Imshow -- Imwrite -- WaitKey -- DestroyAllWindows -- Manipulating images with pixels -- Accessing individual pixels -- Accessing a region of interest (ROI) -- Drawing in OpenCV -- Line -- Rectangle -- Circle -- Text -- Conclusion -- Points to remember -- Test your understanding -- 3. Image Processing Fundamentals -- Structure -- Geometric transformations -- Image translation -- Rotation -- Scaling -- Flipping -- Shearing -- Cropping -- Arithmetic Operations -- Addition -- Subtraction -- Multiplication and division -- Bitwise operations -- AND -- OR -- XOR -- NOT -- Channels and color spaces -- Red Green Blue (RGB) color space -- Blue Green Red (BGR) color space -- Hue Saturation Value (HSV) color space -- Hue Saturation Lightness (HSL) color space -- cvtColor() 67 Hue Saturation Lightness (HSL) color space -- LAB color space -- YCbCr color space -- Conclusion -- Points to Remember -- Test Your Understanding. 4. Image Operations -- Structure -- Morphological operations on images -- Erosion -- cv2.Erode() -- Dilation -- cv2.Dilate() -- Opening -- Cv2.morphologyex() -- Closing -- Morphological gradient -- Top hat -- Bottom hat -- Smoothing and blurring -- Average blurring -- Cv2.blur() -- Median blur -- cv2.medianBlur() -- Gaussian blur -- cv2.gaussianBlur() -- Bilateral filter -- cv2.bilateralFilter() -- Conclusion -- Points to remember -- Test your understanding -- 5. Image Histograms -- Structure -- Introduction to histograms -- cv2.calcHist() -- Matplotlib helper functions -- Histogram for colored images -- Two-dimensional histograms -- Histogram with masks -- Histogram equalization -- cv2.equalizeHist() -- Histogram equalization on colored images -- Adaptive histogram equalization -- Contrast limited adaptive histogram equalization (CLAHE) -- cv2.createCLAHE() -- Histograms for feature extraction -- Conclusion -- Points to remember -- Test your understanding -- 6. Image Segmentation -- Structure -- Introduction to Image Segmentation -- Basic Segmentation Techniques -- Image thresholding -- Simple Thresholding -- cv2.threshold() -- Adaptive Thresholding -- cv2.adaptiveThreshold() -- Otsuâ€™s Thresholding -- Edge and contour-based segmentation -- Advanced Segmentation Techniques -- Watershed Algorithm -- GrabCut algorithm -- cv2.grabCut() -- Clustering-based Segmentation -- Deep Learning-based Segmentation -- Conclusion -- Points to Remember -- Test your understanding -- 7. Edges and Contours -- Structure -- Introduction to edges -- Image gradients -- Filters for image gradients -- Sobel Filters -- cv2.Sobel() -- Scharr Operator -- cv2.filter2D -- Laplacian Operators -- Canny Edge Detector -- cv2.Canny() -- Introduction to Contours -- Contour Hierarchy -- Extracting and Visualizing Contours -- cv2.findContours() -- cv2.drawContours() -- Contour Moments. cv2.Moments() -- Properties of Contours -- Area -- cv2.contourArea() -- Perimeter -- Centroid/Center Of mass -- Bounding Rectangle -- cv2.boundingRect() -- cv2.minAreaRect() -- cv2.boxPoints() -- Extent -- Convex Hull -- cv2.convexHull() -- cv2.polyLines() -- Solidity -- Contour Approximation -- cv2.approxPolyDP() -- Contour Filtering and Selection -- Conclusion -- Points to Remember -- Test your understanding -- 8. Machine Learning with Images -- Structure -- Introduction to Machine Learning -- Overfitting and Underfitting -- Evaluation Metrics -- Hyperparameters and Tuning -- KMeans Clustering -- cv2.kmeans() -- k-Nearest Neighbors (k-NN) -- Feature Scaling -- Hyperparameters -- Logistic Regression -- Hyperparameters -- Decision Trees -- Hyperparameters -- Ensemble Learning -- Random Forest -- Randomness -- Hyperparameters -- Support Vector Machines -- Conclusion -- Points to Remember -- Test your understanding -- 9. Advanced Computer Vision Algorithms -- Structure -- FAST (Features from Accelerated Segment Test) -- cv2.FastFeatureDetector_create -- Harris Keypoint Detection -- cv2.cornerHarris -- BRIEF (Binary Robust Independent Elementary Features) -- cv2.ORB_create -- ORB (Oriented FAST and Rotated BRIEF) -- SIFT (Scale-Invariant Feature Transform) -- cv2.SIFT_create -- RootSIFT (Root Scale-Invariant Feature Transform) -- SURF (Speeded-Up Robust Features) -- Local Binary Patterns -- Histogram of Oriented Gradients -- Conclusion -- Points to Remember -- Test Your Understanding -- 10. Neural Networks -- Structure -- Introduction to Neural Networks -- Design of a Neural Network -- Activation Functions -- Training a Neural Network -- Gradient descent -- Convolutional neural networks -- Layers in a CNN -- Convolutional Layer -- Pooling Layer -- Fully Connected Layer -- Activation Layer -- First Neural Network Model -- Data Loading. Model Instantiation -- Results -- Dropout Regularization -- Neural network architectures -- LeNet -- AlexNet -- VGGNET -- Transfer Learning -- Other Network Architectures -- GoogleNet -- Inception Module -- Architecture -- ResNet -- Conclusion -- Points to remember -- Test your understanding -- 11. Object Detection Using OpenCV -- Structure -- Introduction to object detection -- Detecting objects using sliding windows -- Template matching using OpenCV -- cv2.matchTemplate -- Haar cascades -- Feature extraction for object detection -- Image pyramids -- Facial landmarks with DLIB -- Object tracking using OpenCV -- Conclusion -- Points to remember -- Test your understanding -- 12.Projects Using OpenCV -- Structure -- Automated book inventory system -- Document scanning using OpenCV and OCR -- Face recognition -- Drowsiness detection -- Conclusion -- Index.
Record Nr.	UNINA-9910915788203321