• The Data Analytics of Application Scaling and Why There Are No Giants
    Dr. Neil Gunther, Performance Dynamics Company Agenda 6:30 Doors Open, Food & Networking, Door Prizes from the speaker 7:00 Presentation *** Please arrive by 7:00 PM due to Security *** 8:30 wrap up Live Streaming starts at 7:00pm. Pre-register with this link: https://zoom.us/webinar/register/WN_L8F_38d5QpmjnPSXlXxO4A Event Details Like the 30 ft. giant in 'Jack and the Beanstalk,' myths and fallacies abound regarding application scaling. Many blog posts show some performance data as time-series charts, but otherwise only offer a qualitative analysis. This talk is intended to remedy that by showing you how to QUANTIFY scalability. Time series are not sufficient to assess cost-benefit of cloud services and other scalability trade-offs. After reviewing the nonlinear constraints on the scalability of giants, we apply similar nonlinear data-analytics techniques to determine the universal scalability constraints on such well-known applications as: MySQL, Memcache, NGINX, Zookeeper, and Amazon AWS. Speaker Bio Neil Gunther, M.Sc., Ph.D. is a researcher specializing in performance analysis and capacity planning of large-scale applications. Prior to starting his own consulting company in 1994 (www.perfdynamics.com), Neil worked on the NASA Voyager and Galileo missions, the Xerox PARC Dragon multiprocessor, and the Pyramid/Siemens RM1000 parallel cluster. Neil has authored many technical articles and several books including: "Guerrilla Capacity Planning" (Springer 2007) and the 2nd edition of "Analyzing Computer System Performance with Perl::PDQ" (Springer 2011). Neil is a Senior member of both ACM and IEEE and received the A.A. Michelson Award in 2008.

    Walmart Labs

    860 W California Avenue · Sunnyvale, CA

    15 comments
  • Design and Deployment of Deep Learning with Spark
    This is a one-day, 8 hour bootcamp during which you will cover artificial neural network introduction to getting to production with optimized deployment. Also a chance to win your free business pass for AI Frontier Conference 2018, $1,295 value. TICKETS SIGN UP THROUGH EVENTBRITE Tickets: With discount code MEMBER25OFF, the price will be $100 as a special promotion, through Fri 7pm. NO RSVP on MEETUP, TICKET PURCHASE on EVENTBRIGHT: https://www.eventbrite.com/e/acm-professional-development-seminar-pds-2018-silicon-valley-tickets-50447535938 We are seeking TA's who know ML to help the audience. TA applicants should contact the instructor in advance. Use the [contact] button on the left, send email, phone, LinkedIn and ML experience). PARKING AND ENTRANCE: Both at MLSListings Inc. in the BACK OF BUILDING. PRE-LOADING: BEFORE THE CLASS, PREPARATIONS: For all workshops we will use Jupiter notebooks with Python, Spark and BigDL. Notebook instances will be provided by the organizers. 8 HR CLASS - SUMMARY (detailed outline follows) We will review the design of convolutional neural networks (CNNs) and their history. Why convolutional networks are designed in this particular way; what is the purpose of convolutions, pooling layers and fully connected layers; how CNNs relate to feed-forward (fully-connected) networks. In the workshop section we will apply this knowledge to create a LeNet-5 convolutional network using Spark/BigDL, train the network and use it to recognize handwritten digits from the MNIST dataset. After that we will review the concept of transfer learning — a sophisticated method of applying large convolutional neural networks to real-world problems of recognizing arbitrary images. In the workshop sections we will use BigDL and pre-trained Inception Model and apply transfer learning concepts to recognize images from an arbitrary dataset. You can expect to take-away from the workshop .Theoretical underpinning of Deep Learning technologies . Practical application of DL frameworks to business problems Advanced track to come: .Transfer learning; .Reinforcement Learning; .Generative Adversarial Networks; .Trainers available 1 week after-class office-hour to review your project. TARGET AUDIENCE would include people who ... • are comfortable in programming • may already work on consulting projects or in some technical business problem solving role. • It is helpful if you have tried Python, Spark and BigDL before. CLASS OUTLINE 1) Review of Neural Network Theory (Greg) 2) Intro to Apache Spark Machine Learning (Sujee) 3) Lab 1: Set up the environment, Run first set of SparkML commands (Sujee) 4) Intro to Neural Networks with BigDL (Sujee) 5) Lab 2: Set up BigDL environment, apply NNs to Machine Learning tasks. ~ Lunch ~ 6) Intro to Convolutional Neural Networks (Alex) 7) Lab 3: Image Recognition with BigDL / LeNet and MNIST dataset 8) Intro to Transfer Learning for Image Recognition (Alex) 9) Lab 4: Transfer Learning using BigDL/Spark and Inception Model. -Coffee Break - 10) Design of Convolutional Neural Networks (CNNs) and their History (Greg) 11) Lab 5: Modeling Design with SparkML. Go to TensorFlow Playground (http://playground.tensorflow.org/) to try setting some neural net parameters and training them on different data set. BEFORE THE CLASS, PREPARATIONS: • For fun, play around with some neural nets at the TensorFlow Playground (http://playground.tensorflow.org). This will be covered in the class as well. • You are invited to submit a description of your upcoming machine learning projects or vertical. The instructor will review and may try to incorporate some ideas in the class. Through the meetup site, on the left margin, use the [contact] button. SCHEDULE 8:00 - 8:30 arrive, register, coffee, network 8:30 - 10:00 lecture / lab 15 min break, coffee 10:15 - 11:30 lecture / lab 45 min break for lunch 12:15 -1:45 lecture / lab 15 min break, coffee, small snacks 2:00 - 3:30 lecture / lab 15 min break, coffee, small snacks 3:45 - 6:00 lecture / lab 15 min Q&A ABOUT the Instructors: Sujee Maniyam (https://www.linkedin.com/in/sujeemaniyam) is a seasoned Big Data practitioner and founder of Elephant Scale. He teaches and consults in Big Data technologies (Hadoop, Spark, NoSQL and Cloud) and Data Science. He is an open source contributor and author of 'Hadoop illuminated' (an open-source book on Hadoop) and 'HBase Design Patterns'. Sujee is a frequent speaker at various conferences and meetups. He also advises and mentors various firms. Github : https://github.com/sujee Alex Kalinin (https://www.linkedin.com/in/alexkalinin) leads AI/Machine Learning team at Sizmek - the largest independent buy-side advertising platform. The team develops cutting edge conversion models, recommender systems, models for automatic A/B testing, and many others. These models are applied in real time at scale, with billions of requests processed per day. Previously, Alex worked in both startups and large companies. While at home.ai he led the team to develop home automation algorithms leveraging computer vision and convolutional neural networks. At Yahoo he led the development of the large-scale user acquisitions and analytics system supporting rapid growth of Yahoo Games business. Alex holds MS in Physics degree, and published several papers on image recognition and pattern detection. Greg Makowski (https://www.linkedin.com/in/gregmakowski/) has been deploying data mining models for 25 years as the "neural net guy" at American Express/Epsilon. He has developed the analytic internals and automation for 6+ enterprise software systems or SaaS systems. His first convolutional neural net was trained in 1991, a Time Delay Neural Net for speech recognition. Vertical experience includes financial services (credit card, retail banking, bond pricing, ACH payments, fraud detection, customer relationship management (mail, phone, email, banner), retail supply chain among others. He always has something to learn from everybody.

    MSListing

    740 Kifer Rd · Sunnyvale, ca

  • SDN: Changing Only Everything About Networking (and IT)
    Dr. Dan Pitt, SVP, MEF Forum & President, Palo Alto Innovation Advisors This event will be live streamed by Streaming Volunteer from Seattle, WA. Please register on this link, and login before presentation time. https://zoom.us/webinar/register/WN_cdEtBCVlSPaXrMPP1uiPLQ Agenda 6:30 Doors Open, Food & Networking 7:00 Presentation *** Please arrive by 7:00 PM due to Security *** 8:30 wrap up Event Details It’s been about eight years since Software-Defined Networking (SDN) hit the headlines with a lot of fanfare, initially as a way to disaggregate a Cisco router and reduce the operating expense (Opex) in data centers. Since that time, its more fundamental changes to everything about networking have seeped into not only the technology of networking but the technology of computing and the structure of the IT industry as well. In this talk we will examine some of these impacts, involving technology, business, and people. We will touch on security issues, from the silly to the scary, and even on politically sensitive ones, like the relative importance of the IEEE and ACM. Speakers Bio Dan Pitt is a computer scientist and engineer who has worked mainly in networking and telecommunications with occasional excursions into academia and odd corners of technology (like eye tracking). At present he serves as Senior Vice President of the MEF Forum (formerly Metro Ethernet Forum), a non-profit trade association driving technology and service innovation in the telecom industry, and advises companies (mainly startups) as President of Palo Alto Innovation Advisors. He served as Executive Director of the Open Networking Foundation from its public launch in 2011 through 2016, creating not only the Software-Defined Networking movement but spawning all the derivative Software-Defined Everything Else movements as well. Prior to ONF he ran startup companies in the U.S., Australia, and Canada and served as Dean of Engineering at Santa Clara University. He held executive management roles at Nortel Networks and Bay Networks and prior to that developed and managed networking technology and research at HP Labs in Palo Alto and at IBM in North Carolina and IBM Research in Zurich. He has served on industrial advisory boards at UC Berkeley and the Swiss Federal Institute of Technology. While working for IBM in North Carolina he taught computer science and electrical engineering at Duke and UNC. He holds a B.S. in mathematics from Duke and M.S. and Ph.D. degrees in computer science from the college of engineering at the University of Illinois.

    Walmart Labs

    860 W California Avenue · Sunnyvale, CA

    4 comments
  • Rapid Adoption of Cloud Data Warehouse Technology Using Datometry Hyper-Q
    Agenda 6:30 Doors Open, Food & Networking 7:00 Presentation by Lyublena Antova &Mohamed Soliman *** Please arrive by 6 PM due to Security *** Abstract The database industry is about to undergo a fundamental transformation of unprecedented magnitude as enterprises start trading their well-established database stacks on premises for cloud database technology in order to take advantage of the economics cloud service providers have long promised. Industry experts and analysts expect the next years to prove a watershed moment in this transformation, as cloud databases finally reached critical mass and maturity. Enterprises eager to move to the cloud face a significant dilemma: while moving the content of their databases to the cloud is a well studied problem, making existing applications work with new database platforms is an enormously costly undertaking that calls for rewriting and adjusting of 100’s if not 1,000’s of applications. In this paper, we present a next-generation virtualization technology that lets existing applications run natively on cloud-based database systems. Using this platform, enterprises can move rapidly to the cloud and innovate and create competitive advantage as a matter of months instead of years. We describe technology and application scenarios and demonstrate effectiveness and performance of the approach through actual customer use cases. Speaker Bio Lyublena Antova is a Research Scientist at Datometry, Inc., with expertise in the areas of query optimization, large-scale database systems, and distributed systems and is a founding member of the team that designed and built the Orca query optimizer at Greenplum/EMC/Pivotal. Lyublena’s affection for query optimization began over a decade ago when during a database class she implemented a mini query optimizer and saw the tremendous impact it had on query performance. At Datometry, she is fascinated to find out that the core of the query optimization technology can be applied to a new domain--database virtualization. Lyublena received her B.S. in Computer Science from Sofia University St. Kliment Ohridski (Bulgaria), her M.S. in Computer Science from Saarland University (Germany), and her Ph.D. in Computer Science from Cornell University. Lyublena has 16 peer-reviewed publications, 2 patents granted, and 2 patent submissions to her credit. Mohamed Soliman, Chief Architect Mohamed is Datometry’s Chief Architect with deep expertise in distributed data processing, query processing, distributed data processing, data warehousing. Prior to Datometry, Mohamed was a Staff Engineer at Pivotal Inc. where he worked on building Greenplum’s Orca query optimizer initiative. He has also held senior software engineering positions at Greenplum in the Query Processing team. Mohamed received his B.S. and M.S. in Computer Science from Alexandria University, Egypt, and his Ph.D. in Computer Science (in the database group) from the University of Waterloo, Canada. He is a frequent speaker at top database conferences; has authored or co-authored 22 publications on the science of databases; and has 7 accepted patents and 2 pending patents to his credit.

    PayPal Town Hall

    2161 North First St. · San Jose, CA

    6 comments
  • Relying on Discourse Analysis to Manage Dialogues for a Chatbot
    Dr. Boris Galitsky, Oracle Mobile Cloud Oracle will provide food and offer $500 Credit for anyone who attends and sign up for the Cloud trial on this ACM meetup. Agenda 6:30 Doors Open, Snack & Networking 7:00 Presentation *** Please arrive by 7:00 PM due to Security *** Event Details Chatbots are becoming fairly popular, however, open-source chatbot systems are lagging behind. We introduce a platform for transactional and question-answering chatbot based on machine learning and linguistic analysis of OpenNLP for search engineers and generalists. We will learn how to design a dialogue manager for a given domain as well as how to populate a chatbot with knowledge. The audience will learn how to apply statistical and inductive machine learning to syntactic and rhetoric parsing data. A special focus will be on how to leverage discourse analysis. We will assume that the audience has a basic knowledge of deep learning and machine learning concepts, such as loss function, model training, model inference, and feed-forward conv. neural networks. Speaker Bio Dr. Boris Galitsky contributed linguistic and machine learning technologies to Silicon Valley startups for last 25 years, as well as eBay and Oracle, where he is currently an architect of Intelligent Bots project. An author of two computer science books and 150+ publications, he is now working on a book "Developing Enterprise Chatbots" to be published by Springer in 2019. Boris is Apache committer to OpenNLP where he created OpenNLP. Similarity component which is a basis for chatbot development. https://github.com/bgalitsky

    GWC - RobotX

    4500 Great America Pkwy, Suite 300 · Santa Clara, CA

    4 comments
  • Advanced Image Recognition with Mask R-CNN
    Aniket Rangrej, Data Scientist II, FogHorn Systems Ravi Ilango, Sr Data Scientist, FogHorn Systems This presentation will be live streamed. Please ignore previous version of the link and take the following link. It is best to pre-register. https://zoom.us/meeting/register/3cccef394d4d4ed8d746f627e8486654 Agenda 6:30 Doors Open, Food & Networking 7:00 Presentation *** Please arrive by 7:00 PM due to Security *** 8:30 wrap up Event Details We will cover the progression of deep learning technologies leading up to Mask R-CNN: Convolutional Neural Networks (CNN), Fast R-CNN, Faster R-CNN and Mask R-CNN. Originally, images were labeled with one object name per image, such as "cat". Then, bounding box rectangles were used to label one or more objects within an image. Now, with masking, the irregular outlines of the object are identified in the image, including overlapping instances of the same object. We will also provide a software demo. See also: https://arxiv.org/pdf/1703.06870.pdf (Mask R-CNN paper from Facebook AI Research, 2018) Speakers Bio Aniket is a Data Scientist at FogHorn Systems, solving industrial use cases in computer vision and machine learning. Aniket has done M-Tech in Computer Science and Engineering from Indian Institute of Technology Madras (IIT-M) and has over 7 years of experience in data science, big data and application development. Before joining FogHorn systems, he has worked in Yahoo R&D, Reliance and Hilabs. Aniket has good exposure in text mining and has conference and journal publications in World Wide Web conference and BMC Bioinformatics. https://www.linkedin.com/in/aniket-rangrej-0a661b20/ (Aniket will be presenting from Pune) https://www.linkedin.com/in/raviilango/ Ravi is a Sr Data Scientist at FogHorn Systems, working on a variety of revenue-generating projects for clients involving machine learning and deep learning. He has prior experience as a Sr Data Scientist at Apple for 10 years, and a Sr Program Manager at Applied Materials, among other things. He has an MBA from Santa Clara University, Aeronautics and Production Engineering degree from IIT, Madras, and a number of recent Stanford University ML and AI certificates. (Ravi will be presenting in person, and giving a demo). FogHorn Systems is hiring a data scientist NOW https://www.foghorn.io/data-scientist-2/ We are currently headquartered in Mountain View, moving Oct 1 to Sunnyvale for larger office - to accommodate doubling in size over 2018. To apply, send email to [masked], mentioning in email subject "saw DS job at ACM event". Talk to the hiring manager at the meetup, www.LinkedIn.com/in/GregMakowski. In Feb, the DS team was 3 people, now we are hiring the 10th person. We are hiring 2 more DS people in Pune, India, in Q4.

    Walmart Labs

    860 W California Avenue · Sunnyvale, CA

    6 comments
  • Faster Data Science & Best Practices for Building AI-enabled applications
    Digital transformation demands faster, more productive data science -by Ian Swanson, VP of Product Management AI and ML, Oracle Cloud Software Engineering Best Practices for Building AI-enabled applications -by Rama Akkiraju, Director, IBM Watson Division Agenda 6:00 Doors Open, Food & Networking, 6:45 Registration close 6:30 Presentation by Ian Swanson 7:30 Presentation by Rama Akkiraju *** Please arrive by 6 PM due to Security *** Abstract The key to accelerating digital transformation is deploying quality machine learning solutions faster to operationalize decisions. With this mandate, organizations are racing to hire more data scientists. However, many do not fully realize the value of these teams and face roadblocks trying to scale their efforts. In this talk, we will go over the digital transformation mandate and learn steps you can take today to meet growing demands for AI and machine learning use cases. Speaker Bio Ian Swanson is Vice President of Product Management AI and Machine Learning for Oracle Cloud. In this role, he oversees the product, market, and customer success strategy for Oracle’s Data Science Cloud. The Oracle Data Science Cloud empowers data scientists to deliver the business-changing insights executives expect in less time with self-service access to open source tools, data and computing resources, while also improving the ability of IT teams to support that work. Prior to Oracle, Swanson was CEO and Founder of DataScience.com which was acquired by Oracle, May 2018. DataScience.com provided an industry leading enterprise data science platform that combined the tools, libraries, and languages data scientists loved with the infrastructure and workflows their organizations needed. Earlier in his career, Swanson was an executive at American Express, Sprint, and CEO of Sometrics. Sometrics launched the industry's first global virtual currency platform in 2008 and was acquired by American Express in 2011. That platform -- for which he earned a patent -- managed more than 3.3 trillion units of virtual currency and served an online audience of 250 million in more than 180 countries. Abstract Advancements in computational power, and algorithms has brought Artificial Intelligence (AI) to the forefront in the past decade, taking AI out from 'AI winter'. Many companies and developers are exploring AI as chatbots in customer support scenarios, as doctors' assistants in hospitals, as legal research assistants, as marketing manager assistants, or as real-time face detection in security domain. Building high quality and scalable AI models or services takes specific kind of discipline, methodology and tools. While some of these processes, methods and tools overlap with traditional software engineering practices, several are new to AI domain. In this talk, I will share the best practices for building AI-enabled applications from personal experiences from running AI Operations team at IBM's Watson division. Speaker Bio Rama Akkiraju is a Director, Distinguished Engineer, Master Inventor and IBM Academy Member, at IBM’s Watson Division where she leads the AI operations teams and also heads the AI mission of enabling natural, personalized and compassionate conversations between computers and humans. In her career, Rama has worked on agent-based decision support systems, electronic market places, and semantic Web services, for which she led a World-Wide-Web (W3C) standard. Rama has co-authored 4 book chapters, over 50 technical papers. Rama has over dozen issued patents and 20+ pending. She is the recipient of 3 best paper awards in AI and Operations Research, also multiple awards at IBM. Rama has been named by Forbes as one of the ‘Top 20 Women in AI Research’ in May 2017. Her team’s work has been featured in various media. Rama currently serves as the President for ISSIP, a Service Science professional society for 2018.

    Oracle Building 4 Santa Clara Offices

    4040 George Sellon Circle · Santa Clara, ca

    7 comments
  • What is new on Software I.P. for startups, and how to detect I.P. Theft
    Relevant I.P. updates in 2018 to software start-ups -by Steve Bachmann, Bachmann Law Group Software Forensics: Detecting Software Intellectual Property Theft -by Bob Zeidman, Zeidman Consulting Agenda 6:30 Doors Open, Food & Networking 7:00 Presentation *** Please arrive by 7 PM due to Security *** *** Bring PHOTO ID (passport, driver license, etc.) *** Event Details Technical innovations can make or break a leader in a particular market. Every major and successful software company has a patent portfolio and strategy that has been a key factor in its success. This presentation will focus on the patentability of software as well as why and when an entity should consider pursuing patent protection. We will cover the effects and benefits of patents to software companies, best practices for obtaining patent protection in view of recent patent law developments, and some key pitfalls for start-ups to avoid in obtaining software patent protection. Speaker Bio Steve Bachmann, a Bay Area native, is the founder of Bachmann Law Group PC and specializes in patent and intellectual property matters. For over 18 years, Steve has counseled clients on prosecution of U.S. and foreign patent and trademark applications, implementing trade secret programs, intellectual property (IP) portfolio development and strategy, licensing and technology transfer negotiation and drafting, open source, competitor IP analysis and investigations, and IP related due diligence. Steve has substantial experience in obtaining patent protection in numerous areas of software and hardware.‎ Steve has a worked with start-up and Fortune 500 companies and tailors IP services to each client. http://bachmann-law.com Software Forensics: Detecting Software Intellectual Property Theft Software copyright infringement is a problem of growing concern. Intellectual property theft may be purposeful to gain an unfair advantage over a competitor, or it may be unintended as when a programmer takes code from one project and uses it in another project without first obtaining the appropriate rights. In all cases, a standard measure and standard methodology is needed to be able to effectively compare source code from different programs to determine whether theft or infringement occurred. This talk will examine the algorithms of software code correlation and how it is used to find legitimate and illegitimate copying. Speaker Bio Bob Zeidman is considered a pioneer in the fields of analyzing and synthesizing software source code, the creator of the field of Software Forensics. for having developed software correlation & procedures for identifying copied software code. He is the president & founder of Zeidman Consulting, a premier contract R&D firm in Silicon Valley. He is also the president & founder of Software Analysis and Forensic Engineering Corporation, a leading provider of software intellectual property analysis tools. He is also the president & founder of Zeidman Technologies, where he invented the patented SynthOS® program for automatically generating application specific operating system (ASOS). Bob was named the 2010 and 2015 Outstanding Engineer in a Specialized Field by IEEE for “Innovative Contributions in the Area of Forensic Software Analysis”, also the 2018 Cupertino Innovator of the Year. Bob has been a consultant and testifying expert on over 200 cases involving billions of dollars of intellectual property. An inventor on 22 patents, he has written four engineering books, including "The Software IP Detective’s Handbook". In addition to numerous articles and papers. He has also written three award-winning screenplays and three award-winning novels including his latest, "Good Intentions". Bob has two bachelor's degrees and Master in EE. He is the creator of Silicon Valley Napkin, a cover-all for starters. He is an advisor and board member for several startups and several nonprofit organizations.

    PayPal Town Hall

    2161 North First St. · San Jose, CA

    11 comments
  • Building a new Operating System
    Subhajeet Mukherjee, student, Computer Science, Foothill College (A.S) Agenda 6:30 Doors Open, Food & Networking 7:00 Presentation *** Please arrive by 7 PM due to Security *** Round Focus is a theory to visually demonstrate a problem of ambiguous gestures, multitasking, and notifications that current generation of operating systems have. Subhajeet will address user understanding and security monitoring structures in FreeBSD, OpenBSD, with NetBSD (also Windows NT and Mac OS X's Darwin). His new operating system has included both monolithic and microkernel, as a hybrid kernel. In particular, on system file access, legacy boot and secure boot. He notices that based on the Linux kernel, Android still has some noticeable security issues, including closed source vs open source. Currently it is not efficient enough for the user to "get the job done" anymore. Users do not want their desktops to be bombarded with notifications and unnecessary information. One of the elements of the new operating system includes Timed Notification System, which lets the user interact with the notification for a certain amount of time depending on what the user is working on. Speaker Bio Subhajeet Mukherjee is a 21 year old programmer, and an author. He is currently a student of Computer Science at Foothill College (A.S). He previously completed his freshman year at South Dakota State University. He also has course certification on Machine Intelligence from Stanford University. He has a patent pending in both U.S. and India regarding the method and underlying system of this Operating System. In 2012, he started a debate at TED’s website to discuss about the future of operating systems in Calcutta. In 2016, he received a letter of commitment from Brookings Economic Development Corporation, South Dakota regarding his system. Last year, he received a letter from the Former President of the United States, Barack Obama as he wished him good luck. He is the author of "Not in a Smarter Us" and "Love Without Sensuality". Both books talk about legacy operating systems and the limitation in the current operating systems. LinkedIn: https://www.linkedin.com/in/subhajeet-mukherjee-ba65a36a/ http://subhajeetmukherjee.com

    Walmart Labs

    860 W California Avenue · Sunnyvale, CA

    10 comments