Master the concepts of Deep Learning with experts from IIT
AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions) and self-correction.
Recently, with the advances in the power of computers and easy & large amount of access to the information, it has been made possible to run special algorithms on these tufts of data!
These algorithms are practically parallel human minds, which are able to "think" and compute stuff! This is artificial intelligence!
Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases superior to human experts.
However, life is all about approximations. The recent advancements made in these approximation algorithms and these algorithms which are okay with limited data on the parameters affecting the outcome of a problem have made it possible for computers to defeat humans in chess or in the game of "Go".
With many Deep Learning models, Artificial intelligence already impacts many aspects of our daily lives at work, at home, and as we move about. Over the next decade, the annual Global AI enterprise software revenue will grow from $644 million in 2016 to nearly $39 billion by 2025, and services related revenue should reach almost $150 billion. That proves, Future is AI.
You need to have knowledge of Machine Learning Algorithms in order to do this course. For a complete course on AI from the basics go to Minor Degree Program in AI
For any doubts or concerns please contact the educator of the course Mr Ritesh (+91-9711608586)
Details related to Guaranteed Internship:
i) Why? - We believe acquiring a new skill without working on an actual project is wasteful spending of your time and resources. For your holistic learning experience, both course and internship should be combined.
ii) Who? - An internship is guaranteed by Eckovation to all Eckovation Alumni - those who complete at least a course with us.
iii) Where? - The internship will be either with Eckovation or one of our partner organisations. You will be able to access internship.eckovation.com once you register for a course with us. Our Internship Portal will feature profiles of our alumni and also list internship opportunities by various organisations where alumni can apply.
iv) How many? - The internship will be related to the skill(s) which you've acquired from Eckovation platform. In the case of multiple skills, multiple internship opportunities may be provided.
v) Nature of internship? - The internships will be work from home, i.e., you will be able to work on the internship project from anywhere anytime.
vi) When? - The internship will start only after your course completion in either Summer/December Vacation depending on which comes first. In-semester internships can also be considered on a case-by-case basis.
vii) Certificate - A separate internship certificate will be provided at the end of the internship period. course description
Overview of the course
Revision of Python and ML
Introduction to Neural Networks and Deep Learning
Fully Connected Layer
Optimizers: Adam, SGD, Adamax
Interference and Validation
Overfitting in neural networks
MNIST dataset is famous for its ability to train a model to identify numbers in a particular text. It is the Hello World program of computer vision. Our project here will be Hindi hand writing recognition with the help of such dataset.
Filters: Vertical Edge detector
Horizontal edge detector
Combining filters for complex features
Classification using neural networks
Neural Style Transfer is an open source project where people are able to replicate classic painting styles on their modern age images. It's like using the viral old age filter in FaceApp or create van Gogh painting of your neighbourhood. This project will help you create different effects with any image
RNN for NLP
Instagram is a famous image sharing platform. But a simple image is not enough, you need to have a caption for it to make it look as well as sound cooler. But coming up with cool captions is not always possible on our own. This project will create a program that will generate relevant captions based on your image. Similar programs are in use in the marketing and publicity industry for few years now and having mid blowing captions will make your Insta profile 100 steps ahead of others.
thispersondoesnotexist.com This is a famous website where it shows you pictures of different people. But the catch is, these people does not exist in the real world. They are fake images created by combining multiple images. Though looks like a work of photoshop, this is very complex project and being able to replicate it will get your name in the list top AI experts in the country.
PoseNet is an open source project where the computer identifies your current pose. These poses can be recorded and later used for different purposes. For example, you can use your different actions to control your computer. Play or Pause a video with wave of your hand.
Writing a summary is very important, whether it is report or a story or a news. Not everybody wants to read multiple pages long reports. But writing a good summary is not everybody's forte. This program will help you in that. Best example for this is Inshorts app which gives news in 60 words or less.
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