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IDLI India Deep Learning Initiative

Online session of IDLI



Online session by IDLI

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  • Opinionated GANs by Nishant Sinha - June 24 at 09:30 PM IST Richard Feynman said “What I cannot create, I do not understand”. Given a domain of ob... Read more

  • February 11, 2017 Introduction to Deep Learning - By Dr. Jacob Minz
  • If you have a question about Deep learning such as: What is Deep Learning? What I must know to start work in Deep Learning? What are the basic algorithm in Deep Learning? Why Deep Learning so important? Where I can use Deep Learning? What is the future of Deep Learning? Then this introduction video by [Dr. Jacob minz]( https://w... Read more

  • February 18, 2017 Introduction to Image Classification using Keras - By Malaikannan Sankarasubbu
  • Introduction to Image Classification using Keras Keras is a minimalisitc Python Deep Learning library that works on top of TensorFlow or Theano. It helps to quickly prototype Deep Learning models, and works seamlessly with both CPUs and GPUs. In this talk you will learn about how to build a simple image classification model using Keras. This i... Read more

  • February 25, 2017 GoogleNet Overview Advance - By Auro Tripathy
  • GoogleNet Overview Advance: Auro Tripathy will explain how GoogleLeNet architecture works and how it was made computationaly efficient compared to previous ImageNet winner AlexNet. It introduced Inception module and used 1x1 convolution for reducing computing complexity. This session will be at advanced level. Auro Tripathy founded ShatterLi... Read more

  • March 4, 2017 Linear Algebra basic for Deep Learning - By Prof. Arjit Mondal
  • Linear Algebra basic for Deep Learning - By Prof. Arjit Mondal - Saturday, March 4 at 7:30 AM PST Linear Algebra is the crux of Deep Learning. A good understanding of linear algebra is essential for understanding and working with many machine learning algorithms, especially deep learning algorithms. This session will cover Linear Algebra basics... Read more

  • March 11, 2017 Evolution of convolutional neural networks for image recognition - By Prof. Amit Sethi
  • Evolution of convolutional neural networks for image recognition - By Prof. Amit Sethi Deep learning frameworks, such as convolutional neural networks (CNNs), have almost completely replaced other machine learning techniques for specific tasks such as image recognition using large training datasets. In this webinar, we will go over how CNNs, th... Read more

  • March 18, 2017 Anatomy of Deep Learning Frameworks - Gokul - Saturday, March 18 at 7:30 AM PST
  • Almost all current day DL work happens using Deep Learning frameworks. With so many around, it can get confusing what they are all trying to do. In this talk, I will be discussing how these frameworks work under the hood, how they all use the same concepts and how you could roll your own framework if you desire. I will be covering both high-leve... Read more

  • March 25, 2017 Deep Learning for Speech Recognition by Dr. Sunayana Sitaram
  • Deep Learning for Speech Recognition by Dr. Sunayana Sitaram - Saturday, March 25 at 7:30 AM PST We have recently seen a couple of breakthroughs in speech recognition – Microsoft’s systems have reached human parity in transcribing speech and Baidu’s system is said to be 3 times faster than human transcription for typing text messages, and just ... Read more

  • April 1, 2017 Computational Pathology - An Introduction - By Dr Neeraj Kumar Vaid
  • Computational Pathology: An Introduction - Saturday, April 1 at 9:00 PM IST A talk on computational Pathology by Dr Neeraj Kumar Vaid. He completed his PhD from IIT Guwahati and is currently a visting fellow at Beckman Institute for Advanced Science and Technology. Below is the video on online session: Link of online session : click here! Read more

  • April 8, 2017 Computer Vision for Face Recognition By - Dr. Satya Mallick
  • Computer Vision for Face Recognition By - Dr. Satya Mallick - Saturday, April 8 at 10:00 PM IST Dr. Satya Mallick is the founder of Big Vision LLC, a San Diego, California based company that specializes in computer vision, machine learning, deep learning and artificial intelligence consulting services and products. He is also the principal auth... Read more

  • April 15, 2017 Computer Vision for Face Recognition By - Dr. Satya Mallick
  • Computer Vision for Face Recognition By - Dr. Satya Mallick Dr. Monojit Choudhury is a researcher in Microsoft Research Lab India. He holds a B.Tech and a PhD degree in Computer Science and Engineering from IIT Kharagpur. Monojit’s research interest lies in the intersection of cognition and computation. He has been working on various aspects of... Read more

  • April 22, 2017 How CNNs Localize Objects with Improving Precision and Speed by Auro Tripathy
  • How CNNs Localize Objects with Improving Precision and Speed by Auro Tripathy - Saturday, April 22 at 09:00 PM IST Locating objects in images (a.k.a., detection) quickly and efficiently enables object tracking and counting applications on embedded visual sensors (fixed and mobile). By 2012, progress on techniques for detecting objects in images... Read more

  • April 29, 2017 An Introduction to Reinforcement Learning the doors to AGI By Anirban Santara
  • An Introduction to Reinforcement Learning the doors to AGI By Anirban Santara - Saturday, April 29 at 09:00 PM IST Reinforcement Learning (RL) is a genre of Machine Learning in which an agent learns to choose optimal actions in different states in order to reach its specified goal, solely by interacting with the environment through trial and er... Read more

  • May 6, 2017 Seq2Seq for Predicting PowerTheft By Fenil Doshi and his team
  • Fenil Doshi and his team from SRM Nexttech lab developed a model to predict powertheft to win 1st prize in Smart India Hackathon. In this session, they will give an overview about their Nexttech lab, their motivation to work on powertheft problem, their dataset, their approach and their results. Below is the video of online session lecture... Read more

  • May 13, 2017 DeepLearning as OCR for decoding Indus Valley Manuscripts By Satish Palaniappan
  • DeepLearning as OCR for decoding Indus Valley Manuscripts By Satish Palaniappan - Saturday, May 13 at 09:00 PM IST Of all the ancient inscriptions, the Indus script has long challenged epigraphists, inspite of the various advances in computing, computational epigraphy has not yet been applied to its fullest potential. The main bottleneck here i... Read more

  • May 20, 2017 Trends of AI Research in India - By Neel Shah
  • The goal of this talk is to showcase the results of a recently conducted data-driven study aimed at identifying trends in ongoing research at Indian universities and companies in the areas of AI, ML and DL. To put this in a global perspective, the data will be compared with their international counterparts and some surprising differences will b... Read more

  • June 4, 2017 Adapting Deep Neural Networks between Domains - By Debdoot Sheet
  • Adapting Deep Neural Networks between Domains: from computed retinal angiography to digital pathology to surgical informatics The challenge of trying to use a deep neural network trained on one domain for an application in another domain is quite well known to us, and the challenges are quite intriguing. Most of us have tried using ImageNet per... Read more

  • June 10, 2017 A Brief Introduction to Game Theory and Mechanism Design - By Arpita Biswas
  • A Brief Introduction to Game Theory and Mechanism Design - By Arpita Biswas - June 10 at 09:30 PM IST Game theory can be defined as the “mathematical framework for rigorous study of conflict and cooperation among rational and intelligent agents”. It provides general mathematical techniques for analyzing situations where two or more agents make ... Read more

  • July 24, 2017 Opinionated GANs by Nishant Sinha - June 24 at 09:30 PM IST
  • Opinionated GANs by Nishant Sinha Richard Feynman said “What I cannot create, I do not understand”. Given a domain of objects, say images, generative models try to ‘understand’ the domain well enough to be able to ‘create’ different objects from the domain, on their own or based on instructions. Generative adversarial networks (GANs) are the cu... Read more


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