Selenium Tutorial For Beginners | What Is Selenium? | Selenium Automation Tes...Edureka!
This Edureka Selenium tutorial will give you an introduction to software testing. It talks about the drawbacks of manual testing and reasons why automation testing is the way forward. In this Selenium tutorial, you will also get to learn the different suites of Selenium and what are the features and shortcomings of Selenium as an automation testing tool.
To take a structured course on Selenium, you can check our Selenium training page: https://www.edureka.co/testing-with-selenium-webdriver
Introduction to Selenium | Selenium Tutorial for Beginners | Selenium Trainin...Edureka!
( Selenium Training: https://www.edureka.co/testing-with-selenium-webdriver )
This Edureka tutorial on "Introduction to Selenium" will tell you how testing with Selenium WebDriver works. The following topics have been covered in this tutorial:
1. Pain points of Manual Testing
2. Advantages of Automation Testing
3. Introduction to Selenium
4. Selenium vs other tools
5. Demo: Selenium WebDriver in action
Introduction to Selenium blog: https://goo.gl/b523IO
Selenium Tutorial For Beginners | What Is Selenium? | Selenium Automation Tes...Edureka!
This Edureka Selenium tutorial will give you an introduction to software testing. It talks about the drawbacks of manual testing and reasons why automation testing is the way forward. In this Selenium tutorial, you will also get to learn the different suites of Selenium and what are the features and shortcomings of Selenium as an automation testing tool.
To take a structured course on Selenium, you can check our Selenium training page: https://www.edureka.co/testing-with-selenium-webdriver
Introduction to Selenium | Selenium Tutorial for Beginners | Selenium Trainin...Edureka!
( Selenium Training: https://www.edureka.co/testing-with-selenium-webdriver )
This Edureka tutorial on "Introduction to Selenium" will tell you how testing with Selenium WebDriver works. The following topics have been covered in this tutorial:
1. Pain points of Manual Testing
2. Advantages of Automation Testing
3. Introduction to Selenium
4. Selenium vs other tools
5. Demo: Selenium WebDriver in action
Introduction to Selenium blog: https://goo.gl/b523IO
Cours de Génie Logiciel Avancé
Exposée: Processus de test logiciel
Le test permet de :
- S’assurer que le produit fait ce qu’on attend de lui.
- Identifier les erreurs (programmation ou logique) et les
défaillances dans l’intention de les corriger.
- S’assurer que le produit est conforme à sa spécification.
Agile Testing Framework - The Art of Automated TestingDimitri Ponomareff
Once your organization has successfully implemented Agile methodologies, there are two major areas that will require improvements: Continuous Integration and Automated Testing.
This presentation illustrates why it's important to invest in an Automated Testing Framework (ATF) to reduce technical debt, increase quality and accelerate time to market.
Learn more at www.agiletestingframework.com.
Testing with JUnit 5 and Spring - Spring I/O 2022Sam Brannen
This session will give you an overview of the latest and greatest in the world of testing using JUnit Jupiter (a.k.a. JUnit 5) and the Spring Framework.
The focus will be major new features in JUnit Jupiter 5.8 and 5.9 as well as recent and upcoming enhancements to Spring's integration testing support.
Test Mühendisliğine Giriş Eğitimi - Bölüm 1Mesut Günes
ISTQB ve ISEB Foundation level gibi "Test Uzmanlığı" ile ilgili yapılan sınavlara hazırlık olarak tüketilecek dökümandır. Ayrıca yazılım test mühendisliği ile ilgili bilgi edinmek isteyenlerin okuyabileceği Türkçe kaynaktır.
Now-a-days the world of testing has shifted towards a Continuous Testing model. With increasing digital transformation, Agile & DevOps principles, the need to scale up quality initiatives becomes inevitable. Moreover, with increasing complexity and continuous integration cycles, the frequency of tests to release apps in a shorter time frame with continuous testing becomes the need of the hour to match the speed of Agile & DevOps.
Fast feedback loops and immediate responses allow businesses to adapt to changes in the market quicker than ever before. This is made possible with automation and continuous testing. But how do you achieve continuous testing?
In this, our specialist Sushma Nayak will discuss the present-day best practices in test automation at Knoldus and will examine the key testing trends that focus on the adoption of Continuous Delivery and the evolution of test automation in the coming year.
watch the video of this session on our website: https://www.knoldus.com/learn/webinars
Presentation in the "Whole genome sequencing for clinical microbiology:Translation into routine applications" Symposium , Basel , Switzerland, 2 Sep 2017
Among Viruses, Trojans, and Backdoors:Fighting Malware in 2022Marcus Botacin
My talk at Federal University of Minas Gerais (UFMG) to present some aspects of modern malware research and some of my contributions to the field (derived from my PhD defense). I cover all steps of a detection pipelines: threat hunting, malware triage, sandbox execution, threat intelligence, and endpoint protection.
Cours de Génie Logiciel Avancé
Exposée: Processus de test logiciel
Le test permet de :
- S’assurer que le produit fait ce qu’on attend de lui.
- Identifier les erreurs (programmation ou logique) et les
défaillances dans l’intention de les corriger.
- S’assurer que le produit est conforme à sa spécification.
Agile Testing Framework - The Art of Automated TestingDimitri Ponomareff
Once your organization has successfully implemented Agile methodologies, there are two major areas that will require improvements: Continuous Integration and Automated Testing.
This presentation illustrates why it's important to invest in an Automated Testing Framework (ATF) to reduce technical debt, increase quality and accelerate time to market.
Learn more at www.agiletestingframework.com.
Testing with JUnit 5 and Spring - Spring I/O 2022Sam Brannen
This session will give you an overview of the latest and greatest in the world of testing using JUnit Jupiter (a.k.a. JUnit 5) and the Spring Framework.
The focus will be major new features in JUnit Jupiter 5.8 and 5.9 as well as recent and upcoming enhancements to Spring's integration testing support.
Test Mühendisliğine Giriş Eğitimi - Bölüm 1Mesut Günes
ISTQB ve ISEB Foundation level gibi "Test Uzmanlığı" ile ilgili yapılan sınavlara hazırlık olarak tüketilecek dökümandır. Ayrıca yazılım test mühendisliği ile ilgili bilgi edinmek isteyenlerin okuyabileceği Türkçe kaynaktır.
Now-a-days the world of testing has shifted towards a Continuous Testing model. With increasing digital transformation, Agile & DevOps principles, the need to scale up quality initiatives becomes inevitable. Moreover, with increasing complexity and continuous integration cycles, the frequency of tests to release apps in a shorter time frame with continuous testing becomes the need of the hour to match the speed of Agile & DevOps.
Fast feedback loops and immediate responses allow businesses to adapt to changes in the market quicker than ever before. This is made possible with automation and continuous testing. But how do you achieve continuous testing?
In this, our specialist Sushma Nayak will discuss the present-day best practices in test automation at Knoldus and will examine the key testing trends that focus on the adoption of Continuous Delivery and the evolution of test automation in the coming year.
watch the video of this session on our website: https://www.knoldus.com/learn/webinars
Presentation in the "Whole genome sequencing for clinical microbiology:Translation into routine applications" Symposium , Basel , Switzerland, 2 Sep 2017
Among Viruses, Trojans, and Backdoors:Fighting Malware in 2022Marcus Botacin
My talk at Federal University of Minas Gerais (UFMG) to present some aspects of modern malware research and some of my contributions to the field (derived from my PhD defense). I cover all steps of a detection pipelines: threat hunting, malware triage, sandbox execution, threat intelligence, and endpoint protection.
Pine Biotech conducts monthly informational workshops on the topics related to high-throughput data analysis, interpretation and integration. The workshops highlight our research tools and educational resources developed with collaborators in the US and across the world.
Face Recognition Based Automated Student Attendance Systemijtsrd
Face recognition system is very beneficial in real time applications, concentrated in security control systems. Face Detection and Recognition is a vital area in the province of validation. In this project, the Open CV based face recognition strategy has been proposed. This model integrates a camera that captures an input image, an algorithm Haar Cascade Algorithm for detecting face from an input image, identifying the face and marking the attendance in an excel sheet. The proposed system implements features such as detection of faces, extraction of the features, exposure of extracted features, analysis of students attendance, and monthly attendance report generation. Faces are recognized using advanced LBP using the database that contains images of students and is used to identify students using the captured image. Better precision is accomplished in results and the system takes into account the changes that occurs in the face over some time. Ms. Pranitha Prabhakar | Mr. Kathireshan "Face Recognition Based Automated Student Attendance System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38083.pdf Paper URL : https://www.ijtsrd.com/computer-science/other/38083/face-recognition-based-automated-student-attendance-system/ms-pranitha-prabhakar
Detecting anomalies in security cameras with 3D-convolutional neural network ...IJECEIAES
This paper presents a novel deep learning-based approach for anomaly detec- tion in surveillance films. A deep network that has been trained to recognize objects and human activity in movies forms the foundation of the suggested ap- proach. In order to detect anomalies in surveillance films, the proposed method combines the strengths of 3D-convolutional neural network (3DCNN) and con- volutional long short-term memory (ConvLSTM). From the video frames, the 3DCNN is utilized to extract spatiotemporal features,while ConvLSTM is em- ployed to record temporal relationships between frames. The technique was evaluated on five large-scale datasets from the actual world (UCFCrime, XD- Violence, UBIFights, CCTVFights, UCF101) that had both indoor and outdoor video clips as well as synthetic datasets with a range of object shapes, sizes, and behaviors. The results further demonstrate that combining 3DCNN with Con- vLSTM can increase precision and reduce false positives, achieving a high ac- curacy and area under the receiver operating characteristic-area under the curve (ROC-AUC) in both indoor and outdoor scenarios when compared to cutting- edge techniques mentioned in the comparison.
A small introduction to computer forensics dedicaded to engineering student, organized by 'Club de Sécurité Informatique - Ecole Nationale des Sciences Informatique'
Presentation given by Appistry's Vice President of Product Strategy, Sultan Meghi at the World Genome Data Analysis Summit. Meghi presented about the big data challenges facing labs as they strive to manage the flow of genetic data from sequencer to the clinic.
The systems connected to the network are vulnerable to many malicious programs which threatens the
confidentiality, integrity and availability of a system. Many malicious programs such as viruses, worms, trojan horses, adware,
scareware exists. A new malicious program has gained momentum known as spyware. Traditional techniques such as
Signature-based Detection and Heuristic-based Detection have not performed well in detecting Spyware. Based on the recent
studies it has been proven that data mining techniques yield better results than these traditional techniques. This paper presents
detection of spyware using data mining approach. Here binary feature extraction takes place from executable files, which is
then followed by feature reduction process so that it can be used as training set to generate classifiers. Hence, the generated
classifiers classify new and previously unseen binaries as benign files or spywares.
Automated Live Forensics Analysis for Volatile Data AcquisitionIJERA Editor
The increase in sophisticated attack on computers needs the assistance of Live forensics to uncover the evidence
since traditional forensics methods doesn’t collect volatile data. The volatile data can ease the difficulty towards
investigation in fact it can provide investigator with rich information towards solving a case. Here we are trying
to eliminate the complexity involved in normal process by automating the process of acquisition and analyzing
at the same time providing integrity towards evidence data through python scripting.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
2. 2
演講大綱
Part 1: Orange Data Mining 軟體簡介
Part 2: 糖尿病機器學習檢測案例 / 肺炎 X 光深度學習圖像辨識
Part 3: Orange Data Mining Add-Ons: Bioinformatics and Single Cell
Part 4: Orange Data Mining 參考資料
10. 10
Multilayer Perceptron as a Widget
https://medium.datadriveninvestor.com/different-approaches-to-support-deep-learning-in-a-visual-programming-environment-c5c487ba4c7b
11. 11
Image Embedding as a Widget
https://medium.datadriveninvestor.com/different-approaches-to-support-deep-learning-in-a-visual-programming-environment-c5c487ba4c7b
13. 13
演講大綱
Part 1: Orange Data Mining 軟體簡介
Part 2: 糖尿病機器學習檢測案例 / 肺炎 X 光深度學習圖像辨識
Part 3: Orange Data Mining Add-Ons: Bioinformatics and Single Cell
Part 4: Orange Data Mining 參考資料
26. 26
肺炎 X 光圖像分類 ⸺ Workflow
https://towardsdatascience.com/detecting-pneumonia-in-chest-x-ray-images-under-orange-machine-learning-deep-learning-platform-dd7b6ca6bd4c
27. 27
肺炎 X 光圖像分類 ⸺ Image Viewer
https://towardsdatascience.com/detecting-pneumonia-in-chest-x-ray-images-under-orange-machine-learning-deep-learning-platform-dd7b6ca6bd4c
28. 28
肺炎 X 光圖像分類 ⸺ Image Embedding
https://towardsdatascience.com/detecting-pneumonia-in-chest-x-ray-images-under-orange-machine-learning-deep-learning-platform-dd7b6ca6bd4c
29. 29
肺炎 X 光圖像分類 ⸺ Test and Score
https://towardsdatascience.com/detecting-pneumonia-in-chest-x-ray-images-under-orange-machine-learning-deep-learning-platform-dd7b6ca6bd4c
30. 30
演講大綱
Part 1: Orange Data Mining 軟體簡介
Part 2: 糖尿病機器學習檢測案例 / 肺炎 X 光深度學習圖像辨識
Part 3: Orange Data Mining Add-Ons: Bioinformatics and Single Cell
Part 4: Orange Data Mining 參考資料
34. 34
Cell Clustering And Cluster Analysis
https://singlecell.biolab.si/blog/cell-clustering/
Bone Marrow Mononuclear Cells with AML
35. 35
演講大綱
Part 1: Orange Data Mining 軟體簡介
Part 2: 糖尿病機器學習檢測案例 / 肺炎 X 光深度學習圖像辨識
Part 3: Orange Data Mining Add-Ons: Bioinformatics and Single Cell
Part 4: Orange Data Mining 參考資料
41. 41
演講回顧
Part 1: Orange Data Mining 軟體簡介
Part 2: 糖尿病機器學習檢測案例 / 肺炎 X 光深度學習圖像辨識
Part 3: Orange Data Mining Add-Ons: Bioinformatics and Single Cell
Part 4: Orange Data Mining 參考資料