Learn CNN and Transfer Learning

About this event

We bring one more event for ML enthusiasts.

In the first session we are going to explore Convolutional Neural Network.

A convolutional neural network (CNN) is a specific type of artificial neural network that uses perceptrons, a machine learning unit algorithm, for supervised learning, to analyze data. Convolutional Neural Network is one of the main categories to do images recognition, images classifications. Objects detections, recognition faces etc.

You will learn about

- Computer Vision
- CNN & Types
- Edge Detection
- Construction and Working of CNN
- CNN Architectures
- Data Augmentations
- Transfer Learning
- Object Detections
- YOLO

Speaker : Manthan Ladva

He is exploring M.L. concepts and Now exploring Computer Vision and related frameworks.
He explored CNN and now moving forward for Flutter + TensorFlow + Computer Vision.

Second session we will go deep inside Transfer Learning and will cover following topics.

Transfer learning make use of the knowledge gained while solving one problem and applying it to a different but related problem.

- Transfer Learning Scenarios
- Importance of Transfer Learning
- Transfer Learning Strategies
- Single Task Transfer Learning
- Inductive Transfer Leanring
- Transfer Learning with CNN

Speaker : Hiren Dave

Prerequisites:

Knowledge of basic machine learning algorithms, Python programming language.


Organizers