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BSDA5013 - Deep Learning Practice
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BSDA5013 - Deep Learning Practice
810 words
4 min read
| Field | Value |
|---|---|
| Course Code | BSDA5013 |
| Level | Degree Level Course |
| Credits | 4 |
| Type | Elective |
| Pre-requisites | BSCS3004 - Deep Learning |
📖 Description
-Recognise the full stack of deep learning - datasets, frameworks, hardware for training, deployment across devices, interpretability, and security
-Use tools to improve deep learning practice throughout the entire stack
-Apply best practices in training and deployment, even under constraints of data and hardware
-Build confidence of training models of real-world scale
-Identify problems of social relevance that are solvable with deep learning
🗓️ Weekly Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction to Modern NLP and HF |
| Week 2 | Tokenization |
| Week 3 | Fine-tuning models for downstream tasks |
| Week 4 | Continual Pre-training and Instruction Tuning |
| Week 5 | Spoken Language Identification |
| Week 6 | Speaker Diarisation (identifying speakers and when they are spoken in a conversation) |
| Week 7 | Speech to Text and Text to Speech synthesis |
| Week 8 | Wake word detection like "Hey Google" or "Alexa" with personalization |
| Week 9 | Image Classification |
| Week 10 | Object detection |
| Week 11 | Image based depth estimation |
| Week 12 | Image super-resolution |
📝 About the Instructors
Prof. Mitesh M.Khapra
Associate Professor,
Department of Computer Science and Engineering,
IIT Madras
Mitesh M. Khapra is an Associate Professor in the Department of Computer Science and Engineering at IIT Madras and is affiliated with the Robert Bosch Centre for Data Science and AI. He is also a co-founder of One Fourth Labs, a startup whose mission is to design and deliver affordable hands-on courses on AI and related topics. He is also a co-founder of AI4Bharat, a voluntary community with an aim to provide AI-based solutions to India-specific problems. His research interests span the areas of Deep Learning, Multimodal Multilingual Processing, Natural Language Generation, Dialog systems, Question Answering and Indic Language Processing. Prior to IIT Madras, he was a Researcher at IBM Research India for four and a half years, where he worked on several interesting problems in the areas of Statistical Machine Translation, Cross Language Learning, Multimodal Learning, Argument Mining and Deep Learning. Prior to IBM, he completed his PhD and M.Tech from IIT Bombay in Jan 2012 and July 2008 respectively.During his PhD he was a recipient of the IBM PhD Fellowship (2011) and the Microsoft Rising Star Award (2011). He is also a recipient of the Google Faculty Research Award (2018), the IITM Young Faculty Recognition Award (2019) and the Prof. B. Yegnanarayana Award for Excellence in Research and Teaching (2020).
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Other courses by the same instructor:
BSCS3004 -
Deep Learning
Prof. S. Umesh
Professor,
Department of Electrical Engineering,
Indian Institute of Technology,
IIT Madras
S. Umesh is a Professor of Electrical Engineering at IIT-Madras. He completed his PhD from the University of Rhode Island,USA and his PostDoctoral Fellowship from the City University of New York. He has also been a visiting researcher at AT&T Research Laboratories, USA; at Machine Intelligence Laboratory Cambridge University Engineering Department, UK and the Department of Computer Science, RWTH-Aachen, Germany.
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He is a recipient of the AICTE Career Award for Young Teachers in 1997 and the Alexander von Humboldt Research Fellowship in 2004. During his stint at Cambridge University in 2004, he was part of the U.S. DARPA's Effective, Affordable Reusable Speech-to-text (EARS) programme. Similarly in 2005 he was part of the RWTH-Aachen's TC-STAR project for transcription of speech from European Parliament's Plenary Sessions. Between 2010-2016, he led a multi-institution consortium to develop ASR systems in Indian languages in the agriculture domain which was funded by MeiTY. He is currently leading the ASR efforts for the Natural Language Translation Mission managed by the Office of Principal Scientific Adviser of Govt. of India.
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Visit website
Other courses by the same instructor:
BSEE4001 -
Speech Technology
Dr. Kaushik Mitra
Assistant Professor,
Department of Electrical Engineering,
IIT Madras
Dr. Kaushik Mitra leads the Computational Imaging lab at Indian Institute of Technology (IIT) Madras. He is an Assistant Professor in the department of Electrical Engineering, IITM. Before joining IITM, he was a postdoctoral research associate with Ashok Veeraraghavan at ECE department of Rice University. Here, he worked on framework for analysis of Computational Imaging (CI) systems. Prior to that, he earned his Ph.D in Electrical and Computer Engineering from the University of Maryland, College Park, where his research focus was on the development of statistical models and optimization algorithms for computer vision problems. Currently, his research interests are in computational imaging, computer vision and machine learning.
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