• Introduction to Deep Learning | EVA 3.0 & EIP 4.0

    EVA 1.0 has been an awesome beginning this year, with 350+ professionals joining in. In EVA 1, we are taking people through the depth of AI, and covering the state-of-art concepts in Deep Learning. One of our students recently broke into World's top 6 for CIFAR10 Benchmarks. EVA is designed for working professionals to get a hands-down experience in Vision AI, build a sound career around AI and also progress towards professional research while publishing papers as well. Through EIP we have trained more than 2000 people in deep vision. Soon we are starting EVA Track 3.0 and EIP 4.0, and this session shares the details of the program. This session is for? This session is for those who are serious about Deep Learning and want to build a career as an AI model architect. We will share the step-by-step guide on what resources to follow, how to cover only relevant concepts and how EVA 3.0 (with 6-month schedule) can help you. The session starts on time at 2:00 PM

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  • Introduction to Deep Learning | EIP 4.0 and EVA 2.0

    EVA 1.0 has been an awesome beginning this year, with 350+ professionals joining in. In EVA 1, we are taking people through the depth of AI, and covering the state-of-art concepts in Deep Learning. One of our students recently broke into World's top 6 for CIFAR10 Benchmarks. EVA is designed for working professionals to get a hands-down experience in Vision AI, build a sound career around AI and also progress towards professional research while publishing papers as well. Through EIP we have trained more than 2000 people in deep vision. Soon we are starting EVA 2.0 and EIP 4.0, and this session shares the details of the program. This session is for? This session is for those who are serious about Deep Learning and want to build a career as an AI model architect. We will share the step-by-step guide on what resources to follow, how to cover only relevant concepts and how EVA 2.0 (with 6-month schedule) can help you. The session starts on time at 2:00 PM

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  • Extensive Vision AI Program

    NASSCOM CoE IoT

    Introduction to Extensive Vision AI Program tl:dr; Discussion on what EVA is, and how to join it. If you cannot attend, just visit this link to learn all about EVA: https://docs.google.com/document/d/124hwHEVNOYb7GvDGZZR54BB7x8XmCP5Sr8VU7wjXi0U/edit?usp=sharing ------ Greetings! In the last two years, we have tried our best to provide one of the best learning programs through External Internship Program. Till now we have been able to touch close to 2000 people through EIP. We feel you'd agree that, due to its scale and structure, the program format is fast-paced, and brushes the core concepts, instead of spending time with the participants to go in to further details. We can go much deeper into the concepts and delve much more into the code A lot has also changed in the last year, which needs to be incorporated into the training to make sure that we remain relevant w.r.t. the state of art MLAL practices. In the last four weeks, we have received a lot of request from EIP 3.0 participants to think about an extensive program which can work at reasonable speed, and provide much better support and depth on the concepts. We are happy to announce Extensive Vision AI Program on the same lines. It is exhaustive, runs at a pace similar to a college program, has 30+ hands-on live programming sessions and covers Convolutional Neural Networks, RNN, LSTM, and Reinforcement Learning. If you have attended EIP, you know that we cover only the latest and state-of-art technologies, and EVA is no different. To learn more about the program and how to join it, please refer to this page: https://docs.google.com/document/d/124hwHEVNOYb7GvDGZZR54BB7x8XmCP5Sr8VU7wjXi0U/edit?usp=sharing Please read the details of the program before you visit. This meetup session is designed to go into details of EVA, what all would be covered and program structure. Join us to learn more!

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  • EIP 3.0 Registrations Closed!

    NASSCOM CoE IoT

    [Update]: EIP 3.0 Registrations are closed now. Total 1025 participants this time! Details would be emailed to the selected participants before 16th Feb. [Older content] EIP 3.0, now powered by NASSCOM's CoE IoT & AT and NVIDIA, enrollments starts right now! The course will start tentatively from 18th February. Apart from your extreme drive to learn, no other pre-requisites are required. The resources for this program are provided by NASSCOM, NVIDIA, and Inkers.ai, and is free! Remember, this is a classroom program and seats are limited, so enroll now at www.inkers.ai/eip3 This meetup event is created to announce EIP 3.0. To actually take part in the EIP's 3 months (14-15 classroom session), you must register at the link above.

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  • Implementing AI Research Papers : YOLOv2 End-to-End

    NVIDIA Graphics Pvt Ltd

    Details Implementing ML and DL research papers often provide practitioners with state-of-the-art tools and novel approaches to solving problems, and gives learners new perspectives and solidify understanding of concepts. At this meetup, we will introduce the process of implementing research papers, discuss best practices, parse through an implementation of the YOLOv2 paper for object detection, and set up a process to help participants regularly implement papers. SPEAKER: Rohan Shravan is an ML/AI practitioner since the last 5 years. He has worked on training DNN models for several vision-related problems and regularly contributes back to the ML community through sessions and training. He runs the popular External Internship Program (EIP), an intensive multi-week program that helps program participants develop usable skills in ML. AGENDA: 10:00 - Welcome note 10:15 - Why implement papers? 10:30 - Implementation process and best practices 10:45 - YOLOv2 paper parse-through 12:15 - Common challenges and how to overcome them 12:30 - Resources, more papers, the next steps 12:45 - Sign up for paper implementation group FEE: This meetup is free to attend but registration is required, as given below. REGISTRATION: Applied Singularity Android app users - Register directly on the app, under Events. If you don't have the Android app already, you can get it here: www.appliedsingularity.com/app iOS and others - Please fill in this Event Registration Form: https://goo.gl/forms/JLUR7ls5U1L69T8A3 Note that RSVPing on meetup.com or in the Meetup app DOES NOT reserve your seat. You must register on the Applied Singularity app or fill in the form above. You can see that the Atendee limit is set to 1, because you need to register through the application above. Please reach Nihal at[masked] or at [masked] if you need any clarifications or have any challenges in registration. We look forward to seeing many of you there! This meetup is jointly hosted by Applied Singularity and NVIDIA.

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  • ML/DNN Foundations: Basics

    Stealth Labs

    This is the first of the multi-part DNN meet-up series, where we are planning to cover concepts progressing from basics to advanced. Who should attend: people new to the field of neural networks/CNN-based machine learning domain. Pre-requisites: Open minds. In this session, a laptop is not required. What will we cover? Parallelly we are running a course program called EIP. Many of you might have missed attending the EIP2. In this session, we will cover the grounding concepts required for DNN, equivalent to the 1st session of the EIP. Topics covered are concepts of channels, layers, kernels, convolutions, and embeddings.

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  • Session 1 EIP Content - Animated Journey to ML Basics & 1st DNN

    Who this session is for: 1. Few people from first 4 batches were not able to attend Session 1, this meetup is being conducted to help them go through session 1. 2. If you are from first 4 batches and want to re-cover session 1, then you are invited to attend this. 3. People who missed joining the 7 batches, but wanted to. Visit our website to check out all the content covered in past meetups is available on www.mlblr.com IMPORTANT ANNOUNCEMENT: For the meetup, please bring your laptop and also create an account at https://colab.research.google.com and request for GPU access. Confirming on meetup.com does not confirm your slot! Join us on WhatsApp: ‎Open this link to join my WhatsApp Group: https://chat.whatsapp.com/58w2NFKq68EFFv5wmVzYwU You must log in to SLACK, join MLBLR channel, and confirm on "confirm-hands-on" channel. To join on slack use this link: https://join.slack.com/t/mlblr/shared_invite/enQtMzM5MTM0OTI2ODUwLTE1OGIxOTc1YWFhYzYwMjRhOTFmODEzNzc3NWI3YWU1MTE5NzFiZTdhNzRiZWIwNmY3YWU2MWM3YzRlN2RhNzU

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  • 11th HandsOn: ML BASICS | DENSENET 2018 - WORLDS MOST ACCURATE DNN

    Agenda: 1. The first 2 hours dedicated to ML Basics. 2. This session we introduce DenseNet, the state-of-art DNN - DenseNets have several compelling advantages: they alleviate the vanishing-gradient problem, strengthen feature propagation, encourage feature reuse, and substantially reduce the number of parameters. DenseNets obtain significant improvements over the state-of-the-art on most of them, whilst requiring less computation to achieve high performance. 3. HandsOn on DenseNet, coding and then training DenseNet. Visit our website to check out all the content covered in past meetups is available on www.mlblr.com IMPORTANT ANNOUNCEMENT: For the meetup, please bring your laptop and also create an account at https://colab.research.google.com and request for GPU access. Confirming on meetup.com does not confirm your slot! Join us on WhatsApp: ‎Open this link to join my WhatsApp Group: https://chat.whatsapp.com/58w2NFKq68EFFv5wmVzYwU You must log in to SLACK, join MLBLR channel, and confirm on "confirm-hands-on" channel. To join on slack use this link: https://join.slack.com/t/mlblr/shared_invite/enQtMzM5MTM0OTI2ODUwLTE1OGIxOTc1YWFhYzYwMjRhOTFmODEzNzc3NWI3YWU1MTE5NzFiZTdhNzRiZWIwNmY3YWU2MWM3YzRlN2RhNzU

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  • 10th [Deep] HandsOn: ML FROM SCRATCH | tSNE - We ♡ Embeddings

    Agenda: 1. Like always, the first 1~2 hour is on basics, so you can start from scratch 2. This one is a deep hands-on session, so bring in your laptops. This time we will learn how to run a ResNet model on something it was never trained on, extract embeddings and then see how magically tSNE is still able to cluster these objects contextually! 3. Learn a generalized approach for zero-shot learning! Visit our website to check out all the content covered in past meetups is available on www.mlblr.com IMPORTANT ANNOUNCEMENT: For the meetup, please bring your laptop and also create an account at https://colab.research.google.com and request for GPU access. Confirming on meetup.com does not confirm your slot! Join us on WhatsApp: ‎Open this link to join my WhatsApp Group: https://chat.whatsapp.com/58w2NFKq68EFFv5wmVzYwU You must log in to SLACK, join MLBLR channel, and confirm on "confirm-hands-on" channel. To join on slack use this link: https://join.slack.com/t/mlblr/shared_invite/enQtMzM5MTM0OTI2ODUwLTE1OGIxOTc1YWFhYzYwMjRhOTFmODEzNzc3NWI3YWU1MTE5NzFiZTdhNzRiZWIwNmY3YWU2MWM3YzRlN2RhNzU

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  • 9th HandsOn: ML FROM SCRATCH | SSD IN DETAIL

    Stealth Labs

    Visit our website to check out all the content covered in past meetups is available on www.mlblr.com IMPORTANT ANNOUNCEMENT: For the meetup, please bring your laptop and also create an account at https://colab.research.google.com and request for GPU access. Confirming on meetup.com does not confirm your slot! You must log in to SLACK, join MLBLR channel, and confirm on "confirm-hands-on" channel. To join on slack use this link: https://join.slack.com/t/mlblr/shared_invite/enQtMzM5MTM0OTI2ODUwLTE1OGIxOTc1YWFhYzYwMjRhOTFmODEzNzc3NWI3YWU1MTE5NzFiZTdhNzRiZWIwNmY3YWU2MWM3YzRlN2RhNzU Agenda: 1. Like always, first 1 hour is on basics, so you can start from scratch 2. We will then cover SSD in detail which forms the basis of many modern detectors like MaskRCNN. 3. Code!

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