Deep Learning: Python,OpenCV,CNN,RNN,LST
What you'll learn
- The students will be able to understand what is Deep Learning. How to create various model and solve the problems hands-on using Keras.
- As part of various hands-on activities, students will learn how to apply Deep Learning to real world problems
- Python language
Deep Learning is part of a broader family of machine learning methods based on artificial neural networks.
Deep-learning architectures such as deep neural networks, recurrent neural networks, convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced good results
Artificial neural networks (ANNs) were inspired by information processing and distributed communication nodes in biological systems. ANNs have various differences from biological brains.
Keras is the most used deep learning framework. Keras follows best practices for reducing cognitive load: it offers APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages.
Following topics are covered as part of the course
Explore building blocks of neural networks
Data representation, Tensor, Back propagation
Dataset, Applying Keras to cases studies, over fitting / under fitting
Artificial Neural Networks (ANN)
Convnets (CNN), hands-on with CNN
Text and Sequences
Text data, Language Processing
Recurrent Neural Network (RNN)
Gradients and Back Propagation - Mathematics
Image Processing / CV - Advanced
Image Data Generator
Image Data Generator - Data Augmentation
Intro to Functional API
Multi Input Multi Output Model
The videos are concepts and hands-on implementation of topics
Who this course is for:
- Beginner Python developers, Data Science students, Students who have some exposure to Machine Learning
Shrirang is a Technology expert in product development with international exposure. His more than 25 years of rich experience spans across companies like Bharat Electronics Bangalore (BEL), Tata Elxsi Bangalore/Japan, Philips Software Bangalore/Netherlands, Persistent Systems Pune/Nagpur , ERP based startup. He has handled various overseas customers in countries like USA, Japan, Taiwan, Netherlands and Belgium including working onsite. He was instrumental in starting Technology Incubator at VNIT Nagpur in cooperation with SINE@IIT-Bombay. He also has 10+ years’ experience of campus recruitment and lateral hiring.
He is a mentor for TCS iON program and provides online training for IoT course (via TCS’s iON platform). He was responsible for IoT lab setup at one of the Engineering College. Apart from that he was visiting faculty at VNIT (NIT Nagpur) and other colleges at Nagpur. He conducts training programs for faculties (FDP) and students.
He has authored a book titled "21 IoT Experiments" (Yashwant Kanetkar/ Shrirang Korde).
He also has research publications to his credit including VDAT publication.
His current focus is in technology areas like Machine Learning, Deep Learning, Python & Data Science, Data Structures, C/C++/Java, Internet of Things (IoT) and Android programming.