• Deep Learning for Intelligent Video Analytics Hands-on Workshop

    Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML40 Early bird discount of 40% ends by June 30th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is one of the workshops in Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing ************************************************************************* Instructors: Dr. Kiran Gunnam, Dr. Koji Seto, Dr. Osso Vahabzadeh What you will learn / Topics that will be covered: 1. Intuitive Treatment • Overview of Intelligent Video Analytics and Deep Learning • Convolutional Neural Network (CNN) • Deep Reinforcement Learning and Imitation Learning • Introduction to OpenCV and Apache Spark • Deployment using TensorRT • Applications: Object detection, Action recognition 2. In-depth Treatment • Object detection • Action recognition 3. Hands-on Practice • Object detection 4. Project • Action recognition Target Audiences: Engineers, researchers, practitioners and students who are interested in deep learning and their implementations on GPUs in Intelligent Video Analytics applications. This workshop will particularly benefit people who intend to build Intelligent Video Analytics applications using deep learning techniques on top of a solid understanding of underlying algorithms. Prerequisites: Basic knowledge of Machine Learning, and familiarity with Python and Tensorflow basics Upon completion of this course, you’ll be able to build Intelligent Video Analytics applications using deep learning techniques to start solving real-world problems such as evaluation of real-time video streams by deploying object detection and tracking networks. Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML40 for Early bird discount of 40%! Early bird tickets till June 30th. The above link has an embedded discount code VALLEYML40 to get 40% discount. Early bird tickets (40% discount) last till the end of June. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley

  • [SF Bay ACM] RACE your FACTs: Making AI work for Enterprises

    Co-sponsoring SF Bay ACM Event By Rama Akkiraju, IBM Fellow, Director in IBM’s Watson Division Agenda 6:30 Doors Open, Food & Networking 7:00 Presentation Live Streaming on this link: https://youtu.be/RE13Wsb6j70 *** Please arrive by 7 PM due to Security *** *** Bring PHOTO ID (passport, driver license, etc.) *** Abstract: There is renewed interest among companies these days to implement and deploy AI models in their business processes either to increase automation or to improve human productivity. AI models are making their way as chatbots in customer support scenarios, as doctors' assistants in hospitals, as legal research assistants in the legal domain, as marketing manager assistants in marketing, and as face detection applications in the security domain, just to name a few use cases. Making AI work for enterprises requires a whole new and different set of concerns to be addressed than those for traditional software applications or for consumer-facing AI models such as targeted advertising and product recommendations. These new concerns include robustness (R), accuracy and adaptability (A), continuous learning (C), explainability (E), fairness (F), accountability (A), consistency (C) and transparency (T). In addition, building high quality and scalable AI models requires a specific kind of discipline, methodology, and tools. Data Scientists and practitioners need prescriptive guidance, tools, methods, and best practices on how to procure data, and build, improve and manage their AI models while addressing the concerns mentioned above. In this talk, I will present our best practices for making AI work for enterprises based on our first-hand experience of building scalable AI models for enterprises. Speaker Bio Rama Akkiraju is an IBM Fellow, Master Inventor and IBM Academy Member, and a Director, in IBM’s Watson Division where she leads the AI operations team with a mission to scale AI for Enterprises. Rama also heads the AI mission of enabling natural, personalized and compassionate conversations between computers and humans. Rama has been named by Forbes as one of the ‘Top 20 Women in AI Research’in May 2017, has been featured in ‘A-Team in AI’by Fortune magazine in July 2018 and named ‘Top 10 pioneering women in AI and Machine Learning’ by Enterprise Management 360. 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 and over 100 technical papers. Rama has 18 issued patents and 25+ pending. She is the recipient of 3 best paper awards in AI and Operations Research. Rama holds a Masters degree in Computer Science and has received a gold medal from New York University for her MBA for highest academic excellence. Rama served as the President for ISSIP, a Service Science professional society for 2018 and continues to actively drive AI projects through this professional society.

  • Deep Learning for Robotics Hands-on Workshop

    Z-Park Silicon Valley

    Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML40 Early bird discount of 40% ends by June 30th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is one of the workshops in Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing ************************************************************************* Instructors: Dr. Kiran Gunnam, Dr. Koji Seto, Dr. Osso Vahabzadeh What you will learn / Topics that will be covered: 1. Intuitive Treatment • Overview of Robotics and Deep Learning • Convolutional Neural Network (CNN) • Deep Reinforcement Learning and Imitation Learning • Introduction to ROS and Point Cloud Library (PCL) • Applications: Object Detection, Path Planning • Graph-based Deep Learning (Geometric Deep Learning) 2. In-depth Treatment • Object Detection with CNN • Path Planning using Deep Reinforcement Learning 3. Hands-on Practice • Object Detection 4. Project • Path Planning Target Audiences: Engineers, researchers, practitioners and students who are interested in deep learning and their implementations on GPUs in Robotics applications. This workshop will particularly benefit people who intend to build Robotics applications using deep learning techniques on top of a solid understanding of underlying algorithms. Prerequisites: Basic knowledge of Machine Learning, and familiarity with Python and Tensorflow basics Upon completion of this course, you’ll be able to build Robotics applications using deep learning techniques to start solving real-world problems such as object detection and path planning in autonomous vehicles. Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML40 for Early bird discount of 40%! Early bird tickets till June 30th. The above link has an embedded discount code VALLEYML40 to get 40% discount. Early bird tickets (40% discount) last till the end of June. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley

  • [Free Event] Bigger Brains & Be Agile on Data

    2655 Seely Ave, Cadence Design Systems Inc, San Jose, CA 95131

    Free event- however registration needed at https://www.eventbrite.com/e/building-bigger-brains-utilizing-neuromorphic-engineering-as-the-path-towards-brain-scale-tickets-74536800577?aff=valleyml Organized by: IEEE Computer Society (CS) chapter of Silicon Valley https://computer.ieeesiliconvalley.org/ in benefit of all its members. Sponsors: Computational Intelligence Society (CIS) & ValleyML.ai Speaker #1: Gordon Wilson: CEO and Co-Founder of Rain Neuromorphics Topic #1: Building bigger brains: Utilizing neuromorphic engineering as the path towards brain-scale intelligence. Speaker #2: Patrick Holl Co-founder and CTO of Fusionbase.io Topic #2: Be agile on data and query the world! Location: Cadence, Building 10 Address: 2655 Seely Ave, San Jose, CA 95134 There is a WebEx- please contact us if you are interested to attend remotely.

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  • Deep Learning for Natural Language Processing Hands-on Workshop

    Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML40 Early bird discount of 40% ends by June 30th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is one of the workshops in Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing ************************************************************************* Instructors: Dr. Kiran Gunnam, Dr. Koji Seto, Dr. Osso Vahabzadeh What you will learn / Topics that will be covered: 1. Intuitive Treatment • Overview of Natural Language Processing and Deep Learning • Vector representations of Words: word2vec • Convolutional Neural Network (CNN) • Recurrent neural networks (RNN) • Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) • Recursive neural networks • Deep Reinforcement Learning and Imitation Learning • Applications: Sentence classification, Language modeling, Memory network, Machine translation • Dynamic Memory Networks • Transformer 2. In-depth Treatment • Machine translation with LSTM and GRU • Sentiment analysis with Recursive neural networks 3. Hands-on Practice • Text Classification • Machine Translation 4. Project • Speech Recognition Target Audiences: Engineers, researchers, practitioners and students who are interested in deep learning and their implementations on GPUs in Natural Language Processing applications. This workshop will particularly benefit people who intend to build Natural Language Processing applications using deep learning techniques on top of a solid understanding of underlying algorithms. Prerequisites: Basic knowledge of Machine Learning, and familiarity with Python and Tensorflow basics Upon completion of this course, you’ll be able to build Natural Language Processing applications using deep learning techniques to start solving real-world problems such as Language Translation and Question Answering. Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML40 for Early bird discount of 40%! Early bird tickets till June 30th. The above link has an embedded discount code VALLEYML40 to get 40% discount. Early bird tickets (40% discount) last till the end of June. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley

  • Deep Learning for Computer Vision Hands-on Workshop

    Z-Park Silicon Valley

    Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML40 Early bird discount of 40% ends by June 30th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is one of the workshops in Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing ************************************************************************* Instructors: Dr. Kiran Gunnam, Dr. Koji Seto, Dr. Osso Vahabzadeh What you will learn / Topics that will be covered: 1. Intuitive Treatment • Overview of Computer Vision and Deep Learning • Convolutional Neural Network (CNN) • Deep Reinforcement Learning and Imitation Learning • Generative Adversarial Networks (GANs) • Introduction to OpenCV • Applications: Image Classification, Image Segmentation, Object Detection – Region-based (R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, R-FCN), Single shot (SSD, YOLO), Feature Pyramid Networks (FPN), Image Style Transfer, Image Colorization, Image Reconstruction, Image Super-Resolution, Image Editing, Image Synthesis 2. In-depth Treatment • Real-Time Object Detection: Faster R-CNN, You only look once (YOLO) • Image Synthesis with Generative Adversarial Networks (GANs) 3. Hands-on Practice • CNN - Image Classification • GANs - Image Synthesis 4. Project • Face Recognition Target Audiences: Engineers, researchers, practitioners and students who are interested in deep learning and their implementations on GPUs in Computer Vision applications. This workshop will particularly benefit people who intend to build Computer Vision applications using deep learning techniques on top of a solid understanding of underlying algorithms. Prerequisites: Basic knowledge of Machine Learning, and familiarity with Python and Tensorflow basics Upon completion of this course, you’ll be able to build Computer Vision applications using deep learning techniques to start solving real-world problems such as Healthcare image analysis and Traffic sign classification. Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML40 for Early bird discount of 40%! Early bird tickets till June 30th. The above link has an embedded discount code VALLEYML40 to get 40% discount. Early bird tickets (40% discount) last till the end of June. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley

  • Deep Learning with CNN and Tensorflow

    Z-Park Silicon Valley

    Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML40 Early bird discount of 40% ends by June 30th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is one of the workshops in Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing ************************************************************************* Instructors: Dr. Kiran Gunnam What you will learn / Topics that will be covered: 1. Intuitive Treatment • Overview of Deep Neural Networks and Deep Generative Models - History and early Neural Networks, A visual proof that neural nets can compute any function, Convnet (LeNet), AlexNet, Recurrent Neural Networks, Deep Belief Networks, Autoencoder and Generative Adversarial Networks • Convolutional Layer in Details- Building Block of CNN, Convolutional layer, CNN Architecture Activation functions, Pooling, Normalization, Fully connected layers, Soft-max, Training/Back propagation. • CNN Architecture Optimization in Detail- Overfitting,Data Augmentation, Dropouts, Early stopping, Transfer Learning, Adversarial Training, Effect of Depth, Layer Patterns, Layer Sizing, Kernel size, stride length • CNN Visualization • Case studies of CNN Architectures – LeNet, AlexNet, ZFNet, VGGNet, GoogleNet, Residual Net, MobileNets • Summary and Cautionary words 2. In-depth Treatment • VGGNet and Network Pruning • Inception V4 • MobileNet • Progressive Neural Architecture Search (PNASNet) • Generative Adversarial Networks (GANs) 3. Hands-on Practice • CNN – MNIST (handwritten digits recognition) with Tensorlfow • MobileNet – Transfer Learning for Image Classification with Tensorflow Target Audiences: Engineers, researchers, practitioners and students who are interested in machine learning, deep learning, convolutional neural networks, and their implementations on GPUs. This workshop will particularly benefit people who intend to develop deep learning techniques using CNN and applications that can keep improving themselves after seeing more and diverse data to achieve intelligence. Prerequisites: Basic knowledge of Machine Learning, and familiarity with Python and Tensorflow basics Upon completion of this course, you’ll be able to start solving problems using Deep Learning with CNN such as image classification and will be ready to apply the techniques to real-world problems such as perception for autonomous vehicles. Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML40 for Early bird discount of 40%! Early bird tickets till June 30th. The above link has an embedded discount code VALLEYML40 to get 40% discount. Early bird tickets (40% discount) last till the end of June. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley

  • Classic Machine Learning

    Z-Park Silicon Valley

    Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML40 Early bird discount of 40% ends by June 30th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is one of the workshops in Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing ************************************************************************* Instructors: Dr. Kiran Gunnam What you will learn / Topics that will be covered: 1. Intuitive Treatment • Fundamentals of Machine Learning: Traditional machine learning, Machine learning techniques - Supervised, Unsupervised, Reinforcement, Imitation, Parametric/Non-parametric algorithms, Generative models/Discriminative models • Overview of machine learning algorithms - Linear Regression, Logistic regression, Support Vector Machines, Nearest Neighbors, Decision Trees, Gaussian Mixture Models, Hidden Markov Models, Dimensionality reduction, Recommender system • How to build an end to end application - Understanding challenges and selecting right machine learning algorithm, Data Preprocessing, Evaluating Model • Data Pipelines in Various Applications 2. In-depth Treatment • Support Vector Machines (SVM) • Recommender System 3. Hands-on Practice • Linear Regression • Logistic regression • K-Means algorithm • k-Nearest Neighbor • Decision trees • Support vector machines • Dimensionality reduction • Recommender systems Target Audiences: Engineers, researchers, practitioners and students who are interested in classical machine learning and its implementations. This workshop will particularly benefit people who intend to develop classical machine learning techniques and applications and/or want to pursue a career in data science and machine learning. Prerequisites: Basic knowledge of Linear algebra, Probability, and familiarity with Python and Tensorflow basics Upon completion of this course, you’ll be able to start solving problems using Machine Learning such as medical diagnosis, spam detection, customer segmentation, product recommendation. Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML40 for Early bird discount of 40%! Early bird tickets till June 30th. The above link has an embedded discount code VALLEYML40 to get 40% discount. Early bird tickets (40% discount) last till the end of June. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley

  • Statistical Methods for Data Science

    Z-Park Silicon Valley

    Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML40 Early bird discount of 40% ends by June 30th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is one of the workshops in Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing ************************************************************************* Instructors: Dr. Tirthajyoti Sarkar What you will learn / Topics that will be covered: 1. Descriptive statistics and probability for data analysis 1-1. Why statistics is foundation of data science 1-2. Central tendency and dispersion measures 1-3. Bivariate statistics, scatterplot, and correlation coefficient 1-4. The concept of probability 1-5. Discrete and continuous probability distributions 1-6. Bayes’ rule and how it is used in data science 1-7. Exploratory data analysis (EDA) and how it powers data science 2. Inferential and Bayesian statistics for data science 2-1. What is estimation in statistics 2-2. Concept of p-values 2-3. t-test, ANOVA, Chi-square test 2-4. Bayes’ rule and how to use it for probability computation 2-5. Application example of Bayesian inference using Python 3. Statistical methods as used in practical data science and ML 3-1. Linear regression with practical example 3-2. Linear regression as a statistical inference problem, advanced linear regression topics 3-3. Logistic regression as a classification algorithm, case study with the US income data 3-4. Naïve Bayes concept and practical application – spam filtering 3-5. MLE and k-means clustering using market segmentation example Target Audiences: Engineers, researchers, practitioners and students who are interested in statistics, data science, machine learning, and artificial intelligence. This workshop will particularly benefit people who intend to develop statistical techniques for data science and/or want to pursue a data scientist career. Prerequisites: Basic knowledge of probability, and familiarity with basic programming fundamentals. Upon completion of this course, you’ll be able to start analyzing data using Statistical Methods. Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML40 for Early bird discount of 40%! Early bird tickets till June 30th. The above link has an embedded discount code VALLEYML40 to get 40% discount. Early bird tickets (40% discount) last till the end of June. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley

  • Machine Learning and Deep Learning Boot Camp

    Z-Park Silicon Valley

    *** NO RSVP on MEETUP *** Registration NEEDED at: https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 Discount of 25% ends by August 22nd. http://mldlbootcamp.eventbrite.com/?discount=VALLEYML_MEETUP40 Early bird discount of 40% ends by July 5th. Attendees can get IEEE PDH Certificate from IEEE Continuing Education. This is a Machine Learning and Deep Learning Boot Camp, which is available to register as a complete course of 8 workshops and also as a custom package of individual workshops. Attend this boot camp to build a solid foundation of Machine Learning / Deep Learning principles and apply the techniques to real-world problems. Entire Program schedule along with instructor bios can be downloaded here as a PDF. https://drive.google.com/file/d/1xjiqpf_w0sgHsoU-0NeTHMxCG02DlF-m/view?usp=sharing The Boot Camp consists of the following 8 workshops which cover fundamentals of machine learning to the latest advances of deep learning technologies and their applications. 1. Essential Math, Python and Tensorflow for Machine Learning (Thu, Aug 29, 4 pm – 9 pm) 2. Statistical Methods for Data Science (Sat, Aug 31, 10 am – 6 pm) 3. Classic Machine Learning (Thu, Sep 05, 4 pm – 9 pm) 4. Deep Learning with CNN and Tensorflow (Thu, Sep 12, 4 pm – 9 pm) 5. Deep Learning for Computer Vision Hands-on Workshop (Thu, Sep 19, 4 pm – 9 pm) 6. Deep Learning for Natural Language Processing Hands-on Workshop (Thu, Oct 03, 4 pm – 9 pm) 7. Deep Learning for Robotics Hands-on Workshop (Thu, Oct 10, 4 pm – 9 pm) 8. Deep Learning for Intelligent Video Analytics Hands-on Workshop (Thu, Oct 17, 4 pm – 9 pm) Course Logistics: ValleyML.ai is working with Apollo AI, an approved IEEE Education/Course provider, to offer this course. This event is reviewed and approved by IEEE continuing Education. Please check the Eventbrite page (http://mldlbootcamp.eventbrite.com/?discount=VALLEYML_MEETUP40) or the ValleyML.ai (https://www.valleyml.ai/mldlbootcamp2019) website for more details and FAQ on this offering. Venue: Z-Park Silicon Valley, 4500 Great America Pkwy, Santa Clara, CA 95054 Schedule: Dates for in-person classes: 8/29, 8/31, 9/5, 9/12, 9/19, 10/3, 10/10, 10/17. All the above class hours are from 4 to pm 9 pm on Thursdays except for 8/31 (Saturday) - the class hours are 10 am to 6 pm. For hands-on workshops 5 - 8, you will have a chance to work on a 5-week project, which starts from the fourth week of October and ends in the third week of November. The project instructions are provided every week according to the schedules on the registration page. Instructors: Dr. Kiran Gunnam, IEEE Distinguished Speaker and Distinguished Engineer - Machine Learning & Computer Vision at Western Digital Dr. Koji Seto, Chief Scientist, Apollo AI Inc. Dr. Osso Vahabzadeh, Principal Research Scientist, Apollo AI Inc. Dr. Tirthajyoti Sarkar, Senior Principal Technologist, ON Semiconductor Register at http://mldlbootcamp.eventbrite.com/?discount=VALLEYML_MEETUP40 for Early bird discount of 40%! Early bird tickets till July 5th. The above link has an embedded discount code VALLEYML_MEETUP40 to get 40% discount. Early bird tickets (40% discount) last till July 5th. Regular registration [https://mldlbootcamp.eventbrite.com?discount=VALLEYML25 ] (25% discount code VALLEYML25) period is from July 1st to August 22nd. Late registration [https://mldlbootcamp.eventbrite.com/?aff=vml ] (no discount) starts from August 23rd. Publicity Sponsors: IEEE Signal Processing Society, Santa Clara Valley Chapter ACM San Francisco Bay Area Chapter Silicon Valley Engineering Council Lehigh University Z-Park Silicon Valley