PLEASE NOTE THAT THIS WEBINAR WILL START ON WEDNESDAY, 16 SEPTEMBER, 2020, AT 6:30 PM ***BST (LONDON TIME)*** (1.30 PM ***EDT (NEW YORK TIME)***) TITLE: Software Architecture for AI-intensive Systems ABSTRACT The problem at hand is partly the application of software engineering best practices to AI, but more so the evolution of software engineering to attend to software-intensive systems that contain AI components. BIOGRAPHIES Grady Booch is Chief Scientist for Software Engineering at IBM Research where he leads IBM's research and development for embodied cognition. Having originated the term and the practice of object-oriented design, he is best known for his work in advancing the fields of software engineering and software architecture. A co-author of the Unified Modeling Language (UML), a founding member of the Agile Alliance, and a founding member of the Hillside Group, Grady has published six books and several hundred technical articles, including an ongoing column for IEEE Software. Grady was also a trustee for the Computer History Museum.

Conditional image generation (CIG) is a widely studied problem in computer vision and machine learning. Given a class, CIG takes the name of this class as input and generates a set of images that belong to this class. In existing CIG works, for different classes, their corresponding images are generated independently, without considering the relationship among classes. In real-world applications, the classes are organized into a hierarchy and their hierarchical relationships are informative for generating high-fidelity images. In this paper, we aim to leverage the class hierarchy for conditional image generation. We propose two ways of incorporating class hierarchy: prior control and post constraint. In prior control, we first encode the class hierarchy, then feed it as a prior into the conditional generator to generate images. In post constraint, after the images are generated, we measure their consistency with the class hierarchy and use the consistency score to guide the training of the generator. Based on these two ideas, we propose a TreeGAN model which consists of three modules: (1) a class hierarchy encoder (CHE) which takes the hierarchical structure of classes and their textual names as inputs and learns an embedding for each class; the embedding captures the hierarchical relationship among classes; (2) a conditional image generator (CIG) which takes the CHE-generated embedding of a class as input and generates a set of images belonging to this class; (3) a consistency checker which performs hierarchical classification on the generated images and checks whether the generated images are compatible with the class hierarchy; the consistency score is used to guide the CIG to generate hierarchy-compatible images. Experiments on various datasets demonstrate the effectiveness of our method.

Become a professional Python Developer and get hired Master modern Python 3 fundamentals as well as advanced topics Learn Object Oriented Programming Learn Function Programming Build 12 real world Python projects you can show off Learn how to use Python in Web Development Learn Machine Learning with Python Build a Machine Learning Model Learn Data Science - Analyze and Visualize Data Build a professional Portfolio Website Use Python to process: Images, CSVs, PDFs, and other Files Build a Web Scraper with Python and BeautifulSoup Use Python to send Emails and SMS Use Python to build a Twitter bot Learn to Test, Debug and Handle Errors in your Python programs Learn best practices to write clean, performant, and bug free code Learn to use Selenium and Python in Automation Set up a professional workspace with Jupyter Notebooks, PyCharm, VS Code more Become a complete Python developer! Join a live online community of over 150,000 developers and a course taught by an industry expert that has actually worked both in Silicon Valley and Toronto. This is a brand new Python course just launched September 2019! Graduates of Andrei's courses are now working at Google, Amazon, Apple, IBM, JP Morgan, Facebook, other top tech companies.Learn Python from scratch, get hired, and have fun along the way with the most modern, up-to-date Python course on Udemy (we use the latest version of Python). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Python tutorials anymore.

Beginning C for Arduino, Second Edition is written for those who have no prior experience with microcontrollers or programming but would like to experiment and learn both. Updated with new projects and new boards, this book introduces you to the C programming language, reinforcing each programming structure with a simple demonstration of how you can use C to control the Arduino family of microcontrollers. Author Jack Purdum uses an engaging style to teach good programming techniques using examples that have been honed during his 25 years of university teaching. The C programming language How to use C to control a microcontroller and related hardware How to extend C by creating your own libraries, including an introduction to object-oriented programming During the course of the book, you will learn the basics of programming, such as working with data types, making decisions, and writing control loops. Each chapter ends with a series of exercises and review questions to test your knowledge and reinforce what you have learned.

This is the first part of "Understanding Python" wherein we would be learning the foremost 5 fundamentals in python. Let us jump right into understanding each of them so that at the end of your reading, you will have basic know-how on working with python. Note: All the coding examples provided in this blog are done in the Jupyter notebook which is a web-based platform to work on python. It is highly recommended for learners who want to start with a few lines of code. Python is an object-oriented language and every object is stored in the memory whenever it is instantiated.

As the world’s largest research organization, Nielsen is powered by talented creative scientists. Our Data Scientists come from diverse disciplines such as statistics, research methodology, mathematics, psychology, business, engineering and demography. These professionals drive innovation, new product ideation, experimental design and testing, complex analysis and delivery of data insights. This position is responsible for independently analyzing, developing, testing, and supporting moderate to highly complex application software as they relate to Statistical Methods and Models. These software algorithms, prototypes and tools must be developed as part of a statistical team and maintained with high-quality standards and minimal defects. Analyzes, designs, and documents software tools as they relate to big data sets : Investigates and analyzes verbal and written requests for software, interpreting application requirements to construct moderate to highly complex tools. Designs moderate to highly complex software code and test plans, ensuring software developed meets requirements. Writes technical documentation for routines and tools, facilitating their maintenance. Work directly with cross functional teams to define and implement analytical models as part of the overall product: Parse and manipulate raw, complex data streams to prepare for loading into analytical tools. Work with senior statisticians to define and implement analytical models as part of the overall methodologies being implemented. Design and implement models that scale and perform well in large scale, data heavy applications. Develop and tests algorithms, prototypes and technical specifications that will be used for new products and enhancements to existing products. Strong analytical skills including analysis, data collection, process mapping and troubleshooting for root cause. The ability to work in a fast-paced multidisciplinary environment as in a every changing landscape where new data keeps flowing in rapidly. Provides support to internal users and support staff: Investigates tool incidents for missing or incorrect functionality. Assesses incident resolution and estimates application changes. Applies resolutions, leading to timely, error free revisions in applications. Participates on project teams: Participates in ensuring the project team is following and continuously improving the information technology (IT) software development lifecycle (SDLC) as they relate to prototypes and tools. Conducts and participates in technical reviews of moderate to highly complex software tools, evaluating the proposed technical solutions and recommending appropriate revisions for efficiency and maintainability. Investigates and develops application impact and cost estimates for new tools and models enhancements, providing input into the project work plan. Contributes to measuring application size and effectiveness by participating in function point counting, milestone tracking, and defect tracking initiatives, ensuring assignment completion by the required dates. Assist with the transition of methodologies to Operations or Application Development. Researches, assesses, and facilitates the adoption of new technologies: Contributes to proposals and recommendations of technical innovations, which could benefit our organization. Contributes to the evaluation of new methods and technologies. Qualifications Requirements Bachelor’s degree in computer science or statistics, or equivalent work experience. Minimum of two years’ experience in software development as it relates to data mining or model development. Experience in some of these technologies: C++, Java or any similar object oriented language. Experience with data-intensive applications: SAS, R or Python. Minimum of two years’ experience in software development as it relates to SQL, Java, R or Python. Desire to analyze large data sets, find the truth in data, and develop efficient processes for data analysis. Expert ability to apply analytical and problem-solving skills to solve complex design and coding problems. Advanced knowledge of one or more software development languages and proficiency in the use of utilities, batch processing, and online processing. Advanced knowledge of one or more file access methods and database management systems. Working knowledge of the appropriate operating systems and communication interfaces. Advanced understanding of and the ability to apply software design and testing principles. Good interpersonal skills. ABOUT NIELSEN Nielsen is a global performance management company that provides a comprehensive understanding of what consumers Watch and Buy. Nielsen's Watch segment provides media and advertising clients with Total Audience measurement services across all devices where content — video, audio and text — is consumed. The Buy segment offers consumer packaged goods manufacturers and retailers the industry's only global view of retail performance measurement. By integrating information from its Watch and Buy segments and other data sources, Nielsen provides its clients with both world-class measurement as well as analytics that help improve performance. Nielsen, an S&P 500 company (NYSE: NLSN), has operations in over 100 countries that cover more than 90% of the world's population. Nielsen prides itself on being a place where employees can be themselves, make a difference, and grow their careers with the company. It has been named one of the “Top 50 Companies for Diversity” by DiversityInc for three years running and was selected as one of the “Top 35 Companies for Leaders who want Flexibility” by FlexJobs. For more information visit www.nielsen.com . Nielsen is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Job : Data Science Primary Location : North America-US-IL-Schaumburg Other Locations : North America-US-FL-Tampa Bay Organization : Data Science Schedule : Full-time Shift : Day Travel : Yes, 20 % of the Time

This chapter describes how the SP System, meaning the SP Theory of Intelligence, and its realisation as the SP Computer Model, may promote transparency and granularity in AI, and some other areas of application. The chapter describes how transparency in the workings and output of the SP Computer Model may be achieved via three routes: 1) the program provides a very full audit trail for such processes as recognition, reasoning, analysis of language, and so on. There is also an explicit audit trail for the unsupervised learning of new knowledge; 2) knowledge from the system is likely to be granular and easy for people to understand; and 3) there are seven principles for the organisation of knowledge which are central in the workings of the SP System and also very familiar to people (eg chunking-with-codes, part-whole hierarchies, and class-inclusion hierarchies), and that kind of familiarity in the way knowledge is structured by the system, is likely to be important in the interpretability, explainability, and transparency of that knowledge. Examples from the SP Computer Model are shown throughout the chapter.

Python is like Heath Ledger in the programming world. Who does even hate Heath Ledger? Python is just like that in the developer community these days. Python is an English like, general-purpose, object-oriented programming language created by Guido Van Rossum initially released in 1991 named after a TV show that he loved named - Monty Python's Flying Circus. We love Python and You should also love Python.

Created by Bluelime Learning Solutions Students also bought Interactive Web Animations [JavaScript, SVG, CSS & HTML] Bootstrap 5 Course: The Complete Guide (Step by Step) WordPress & WooCommerce Course: Complete Guide to E-Commerce IP Addressing and Subnetting - Hands-on Learning Approach SQL with PostgreSQL For Beginners Preview this course GET COUPON CODE Description Python is a dynamic modern object -oriented programming language and can be used to do a lot of things both big and small. Python is what is referred to as a high level language. That means it is a language that is closer to humans than computer.It is also known as a general purpose programming language due to it's flexibility. Python is an interpreted language that does not need to be complied like for example java programming language. It is interpreted and run on the fly the same time.

The user experiences of functional programming languages sucks. No doubt, this is a sad but true story for most functional programming (FP) languages. I personally thought that FP languages like Haskell offers a very unified and pure programming concepts (i.e. However, Haskell syntax is a mess (take a look at the grammar), there are a lot of edge cases (e.g. Of course this problem is not only limited to Haskell, similar problems can also be found in other FP languages like Erlang, F#, OCaml etc.