Pytorch Advanced Deep Learning (Computer Vision, DataAug)

What you'll learn
Deep Unsupervised Visual Representation Learning Techniques
Deep Learning in Unsupervised manner
Computer Vision
Deep Learning for Computer Vision
Learn how companies like Google, Facebook build production level models
Basics of Pytorch & Numpy
Awesome SOTA Data Augmentation techniques in pytorch
Various properties of Softmax and CrossEntropy in Numpy & Pytorch
SimCLR (Simple Contrastive Learning)
Supervised contrastive learning
Non Parametric Instance Level Learning
Image Search and Cluster Search
Faiss Search
noise contrastive estimator
contrastive learning
SOTA papers like RandAug, JigSaw, PEARL, SimCLR, SupCon and many more..
Similarity metric like Cosine euclidean in Pytorch

Description
Published in 2021: Alpha Release

Dedicated to my Late Father KPS

You can take this course risk-free and if you don't like it, you can get a refund anytime in the first 30 days!

Welcome to the Deep Unsupervised Visual Representation learning (DUVRL) and SOTA Data Augmentation in Pytorch & Numpy

Deep Unsupervised Learning is very niche skill and it is being heavily used in production by AI superstar companies like Google, Amazon, Facebook, as a matter of fact lots of ideas we will talk about. in this course are being used to build SOTA products like Shop the Look or Face Search, Speech to emotion detection etc.

To learn Deep Learning and Deep Unsupervised Visual Representation learning step-by-step, you have come to the right place!

Deep Learning is Easy to learn, if you know basic Math and can code..

Thanks to my several years of experience in Deep Learning, I wanted to make Deep Unsupervised Learning to everyone.

We'll take a step-by-step approach to learn all the fundamentals of Unsupervised Visual Representation learning.

At the end of this course, you'll be productive and you'll know the following:

Unsupervised Visual Representation learning

Numpy

Pytorch

pytorch

pytorch Tensor API

pytorch Tensor Manipulation

Intro to Torch.NN

pytorch Autograds and gradients

pytorch Vision training pipeline

torchvision pretrained model load

pytorch Quiz

Image Search

Cluster Search

Faiss Search

PEARL

NPILD

JigSaw

SimCLR

SupCon

How to do image search and scale

Note: The Hands on section is written in python 3.6, pytorch, numpy which is defacto now a days for deep learning. But the concepts covered in the course is also applicable if you use tensorflow or other equivalent libraries.

Although the code is Computer Vision heavy but these ideas can also be applied to Speech and NLP.

You can take this course risk-free and if you don't like it, you can get a refund anytime in the first 30 days!

Instructor

The instructor of this course have more than 15+ years of experience in Machine learning and deep Learning, and worked with people from Google Brain team. The instructor also hold multiple patent in the area of machine learning and deep learning.

Fish.AI is in stealth mode early stage start up as of 2021.


This Course Also Comes With:

Lifetime Access to All Future Updates

A responsive instructor in the Q&A Section

Links to interesting articles, and lots of good code to base your next applications onto

Udemy Certificate of Completion Ready for Download

This is the course that could improve your career!

Computer vision is a niche skill. Especially if you know deep learning unsupervised approches.

All the papers and ideas presented in this course are used by production level AI products. the skills you acquire in this course will definitely help you in lots of computer vision applications.

I hope to see you inside the course!

Who this course is for:

AI application Developers who want to built cool vision based applications

AI application Developers who want to learn unsupervised way of deep learning

Any Developers who wants to build face recognition, object detection, image search , apparel recognition, speech recognition based products

AI Architects who want to develop state of the art vision products

Anyone looking to learn the theory of deep unsupervised visual representation learning

Happy learning!

Who this course is for:
Developer who are interested in building AI/Deep Learning products
Architects who are interested in building AI//Deep Learning products
Developer and AI Developer who are interested in Data Augmentation Technique
Developer and AI Developer who are interested in Computer Vision, Deep Learning, Deep Unsupervised Learning

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