February 5, 2022
6:00 pm
Event Code: TWIMM171221
Registration Starts: October 2, 2021
Last Date of Registration: January 30, 2022
Date: February 05, 2022 to February 11, 2022
Timing: 6:00PM to 7:30PM (IST)
Machine learning in recent times has been at the forefront of technological advancements pushing the boundaries of many established ideas and beliefs in fields ranging from basic science to space technologies. This workshop walks you through the journey of practical machine intelligence and deep learning introducing the theoretical aspects followed by the practical applications and hands-on training. It is useful for students, researchers and faculty working in interdisciplinary areas.
In the end, the top three participants will be selected for the award of appreciation on the basis of their scores. The evaluation process will include score assignments, presentations and a project to the registered participants only. These awards will be only for UG & PG students and research scholars only
The workshop will be held throughย Cisco Webex. All the sessions will be hands-on practical and implementation-based. Recording and presented contents will be provided to each registered participant. The timing of each session will be 6:00 PM to 7:30 PM each day. International Participants are requested to fix their local time with IST.ย Click here for world clock. Limited seats are available.ย Certificate to each registered participant will be given after attending successfully.
Machine Learning:ย What Is Machine Learning?, ย Challenges with Machine Learning, ย Over fitting, ย Confronting ย Over fitting, ย Types of Machine Learning , Classification and Regression
Neural Network:ย Nodes of a Neural Network, Layers of Neural Network, Supervised Learning of a Neural Network, Training of a Single-Layer Neural Network- Delta Rule, Generalized Delta Rule, SGD, Batch, and Mini Batch, Stochastic Gradient Descent, Batch, Mini Batch, Implementation of the SGD Method , Implementation of the Batch Method, Comparison of the SGD and the Batch, Limitations of Single-Layer Neural Networks.
Training of Multi-Layer Neural Network:ย Back-Propagation Algorithm, Example: Back-Propagation, XOR Problem, Momentum, Cost Function and Learning Rule, Example: Cross Entropy Function, Cross Entropy Function, Comparison of Cost Functions
Neural Network and Classification:ย Binary Classification, Multiclass Classification, Example: Multiclass Classification
Deep Learning:ย Improvement of the Deep Neural Network, Vanishing Gradient, Over fitting, Computational Load, Example: ReLU and Dropout, ReLU Function Dropout
Convolution Neural Network:ย Architecture of ConvNet , Convolution Layer, Pooling Layer, Example: MNIST
Category | Indian | International |
Student | 300 Rs | 20 USD |
Faculty | 800 Rs | 50 USD |
Research Scholar | 500 Rs | 40 USD |
Member of MTTF | 400 Rs | 30 USD |
Coordinators of MTTF | 0 Rs | 0 USD |
Note:ย The benefit of MTTF Membership will be given to those, who registered on or before September 1, 2021
Interested participant for this event has to pay first registration fee. To pay registration fee there are three different methods i.e. Paypal, Payumoney and MTTF Bank Account. International participants can pay through Paypal or MTTF Bank Account. Indian participant can use Payumoney or MTTF Bank account. Transaction number and event code is necessary in registration form.
Event Code:ย TWIMM171221
International:ย ย Click here
Indian :ย Click here
MTTF-Bank Account:ย Click here
Organized by
Feel free to contact us for any query
Email:ย organizingsecretary@batthziraptyltd.com
Whatapp: +91-798-646-1434
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