infyni

About Course

This live online training in Deep Learning with Computer Vision & NLP is organized by NRIVA for members only. The training will cover the following :

Introduction to AI and Deep Learning
Deep Learning essentials
Pytorch Basics
Introduction to Images & OpenCV Basics
Convolutional Neural Networks
Recurrent Neural Network
Transformers, BERT & GPT
NLP using Spacy

The following prerequisites will be needed prior to our training :

Python Programming
Basic understanding of Machine Learning
Basics of Statistics

Course Offerings

Instructor-led interactive classes
Clarify your doubts during class
Access recordings of the class
Attend on mobile or tablet
Live projects to practice
Case studies to learn from
Lifetime mentorship support
Industry specific curriculum
Certificate of completion
Employability opportunity

Topics
Instructor (1)
Reviews

1 Prerequisites

Python programming
Good understanding of Machine Learning concepts
Statistics basics
Understanding of 12th Standard mathematics

2 Introduction to AI and Deep Learning

Introduction to Deep Learning
Working of a Deep Network
History and evolution of various deep learning algorithms
Why Deep Learning

3 Deep Learning Essentials

What is Perceptron
What is Neuron
Sigmoid neuron
Activation functions
Cost function
Optimization
Dense networks
Regularization
Layered structures and Types of layers
Forward pass
Back propagation - chain rule and evaluation metrics
Gradient Descent
SGD (for a SoftMax classifier example)
Nestorov's momentum
RMSProp
Adam

4 Pytorch Basics

Computational Graph and Deep Learning framework
Pytorch installation
Torch Tensors & Numpy bridge
Automatic Differentiation
Loss Functions
Weigh Initialization
Regression with Deep learning
Classification with Deep Learning

5 Introduction to Images and OpenCV Basics

Opening Image files using Python
Opening Image files with OpenCV
Drawing on Images - Basic Shapes
Drawing on Images - Text and Polygons
Direct Drawing on Images with a mouse

6 Convolutional Neural Networks

Introduction to CNN (Convolutional Neural Networks)
Applications of CNN
CNN Architecture
Convolution
Pooling layers
CNN illustrations
Image classification with CNN
Object detection and image segmentation

7 Recurrent Neural Network

Fundamentals of RNN (Recurrent Neural Network)
Applications of RNN
Modelling sequencing
Types of RNNs - LSTM, GRU

8 Transformers, BERT & GPT

Transformers Architecture
BERT – State of the art NLP technique

9 NLP using Spacy

Getting started with SpaCy
Core operations with SpaCy
SpaCy features
Linguistic features
Rule based matching
Working with word vectors and semantic similarity

Shravan K

About Instructor

Shravan Kumar is a Principal Consultant for 10+ organizations with over 8 years of experience in implementing Data Science, Machine Learning, and Artificial Intelligence. Shravan is also an IIT certified trainer and mentor who has trained over 5000 students. He is an expert in the Time series and NLP domain and has successfully implemented numerous projects for various Indian and US companies.

4.0

Ratings

13

Reviews

452

Students

3

Courses

(13)

"I'm grateful for this course; it's expanded my understanding of AI. The explanations were straightforward, making complex topics accessible."

Sreekanth Uppala

Dec. 22, 2023, 3:53 p.m.

"I appreciated the depth of knowledge shared in this course. Despite occasional language barriers, the content was well-structured and easy to follow."

Vijay Tatikonda

Dec. 22, 2023, 3:52 p.m.

"Great course overall. The concepts were presented logically and clearly. However, a bit more emphasis on practical applications would have been beneficial."

Santhosh Pajjuri

Dec. 22, 2023, 3:52 p.m.

"The course was enriching and gave me a new perspective on AI. The practical exercises were particularly helpful in solidifying the learning."

Mohana Sudhir Kollipara

Dec. 22, 2023, 3:51 p.m.

"Informative content and good explanations, although at times, it felt a bit fast-paced for someone like me who's relatively new to these concepts."

Siva Kumar Puram

Dec. 22, 2023, 3:51 p.m.

"I thoroughly enjoyed the course! The instructor made the subject matter approachable, and I feel more confident in my understanding of AI and its applications."

Soma Mahesh

Dec. 22, 2023, 3:50 p.m.

"Overall, a good experience. The course content was comprehensive, but sometimes it felt a bit challenging to keep up, especially with the technical aspects."

Shabdika Gubba