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Complete Python Based Image Processing and Computer Vision

Computer Vision Python : Image Recognition & Manipulation : Deep Learning Computer Vision Python : Image Analysis Python

4.24 (440 reviews)

Students

5.5 hours

Content

Dec 2019

Last Update
Regular Price


What you will learn

Install and Get Started With the Python Data Science Environment- Jupyter/iPython

Read In Image Data Into The Jupiter/iPython Environment

Carry Out Basic Image Pre-processing & Computer Vision Tasks With python

Implement Unsupervised Learning Algorithms (such as PCA) on Image Data

Implement Common machine learning Algorithms on Image Classification

Implment Deep learning Algorithms on Imagery Data

Learn To get Started With Tensorflow and Keras For Image processing With deep learning


Description

Complete Python Based Image Processing and Computer Vision With Conventional Techniques, Data Science and Deep Learning

THIS IS A COMPLETE PYTHON-BASED IMAGE PROCESSING & COMPUTER VISION COURSE !

It is a full  Python-based image processing and computer vision boot camp that will help you implement basic image processing and computer vision tasks using Jupyter Notebooks.                         

HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:

This course is your complete guide to practical image processing and computer vision tasks using Python..

This means, this course covers the important aspects of Keras and Tensorflow (Google's powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Tensorflow and Keras based data science.  

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of Tensorflow and Keras is revolutionizing Deep Learning...

By gaining proficiency in Keras and and Tensorflow, you can give your company a competitive edge and boost your career to the next level.

THIS IS MY PROMISE TO YOU: COMPLETE THIS ONE COURSE & BECOME A PRO IN PRACTICAL KERAS & TENSORFLOW BASED DATA SCIENCE!

But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life data from different sources  using data science related techniques and producing publications for international peer reviewed journals.

 Over the course of my research I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning..

This gives students an incomplete knowledge of the subject. My course, on the other hand, will give you a robust grounding in all aspects of data science within the Tensorflow framework.

Unlike other courses, we dig deep into both the conventional and data science-centric image processing and computer vision tasks! After learning the most important image processing and computer vision tasks, you will learn to implement both machine learning and deep learning techniques in a hands-on manner. You will be exposed to real life data and learn how to implement and evaluate the performance of the different data science packages, including Keras.

DISCOVER 8 COMPLETE SECTIONS ADDRESSING EVERY ASPECT OF PYTHON BASED IMAGE PROCESSING & COMPUTER VISION

• Detailed introduction to using the powerful Python driven framework for data science Anaconda for image processing and computer vision tasks
• Jargon-free introduction to the relevant theoretical concepts
• Detailed introduction to installing and using the relevant packages including tensor flow and Keras
• Implement Machine Learning algorithms, (both Supervised Learning and Unsupervised Learning ) on real life image data
• You’ll even discover how to create artificial neural networks and deep learning structures to implement on imagery data with Tensorflow & Keras

• Introduction to transfer learning


BUT,  WAIT! THIS ISN'T JUST ANY OTHER DATA SCIENCE COURSE:

You’ll start by absorbing the most commonly used image processing and computer vision basics and techniques.

I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts. This means you get a jargon free introduction to the much-needed theoretical concepts

My course will help you implement the methods using real imagery data obtained from different sources. Many courses use made-up data that does not empower students to implement Python based image processing in real -life.

After taking this course, you’ll easily use image processing and computer vision packages such as OpenCV along with gaining fluency in Tensorflow and Keras. I will even introduce you to deep learning models such as Convolution Neural network (CNN) and their implementation for imagery classification !!

The underlying motivation for the course is to ensure you can apply Python based data science techniques on real image data into practice today, start analyzing  data for your own projects whatever your skill level, and impress your potential employers with actual examples of  abilities.

It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to image processing and computer vision (and assocaited data science methods). However, majority of the course will focus on implementing different  techniques on real data and interpret the results..

After each video you will learn a new concept or technique which you may apply to your own projects!

JOIN THE COURSE NOW!

#computer #vision #python #image #processing #analysis


Screenshots

Complete Python Based Image Processing and Computer Vision
Complete Python Based Image Processing and Computer Vision
Complete Python Based Image Processing and Computer Vision
Complete Python Based Image Processing and Computer Vision

Content

Computer Vision with Python - Introduction to the Course

Python Image Processing & Computer Vision - Welcome

Data and Code

Get Started With the Python Data Science Environment

For Mac Users

Introduction to iPython/Jupyter

Working With Colabs

Python Image Analysis - Getting Started With Basic Image Processing in Python

What Are Images?

Read in Images in Python

Some Basic Image Conversions

Basic Image Resizing

What is Interpolation? A Geographic Perspective

Basic Image Transformations

Contrast Stretching

Filtering Images

Introduction to Computer Vision

What is Computer Vision?

Read in Images Using OpenCV

Image Filtering With OpenCV

Edge Detection With OpenCV

More Edge Detection: Sobel Method

Corner Detection

Face Detection With Haar Features: Theory

Face Detection

Image Recognition - What is Machine Learning?

Introduction to Some Concepts

Unsupervised Learning Methods

What is Unsupervised Learning?

Theory Behind PCA

Implement PCA on Images

PCA For Image reconstruction

Randomised PCA

Theory Behind K-means

K-Means For Image Reconstruction

Classify High Dimensional Data With t-SNE

Practical Case Study: Identify Flowers

Cluster the Flowers: Read in Images

Implement PCA

Implement t-SNE

Supervised Learning: Classifying Images

Brief Introduction to Supervised Learning

Implement SVM to Classify Digits

Accuracy Assessment

Implement RF to Classify Digits

Start With Deep Learning

Why Deep Learning?

Written Tensorflow Installation Instructions

Install Keras on Windows 10

Install Keras on Mac

Written Keras Install Instructions

Deep Learning For Image Classification

Introduction to CNN

Implement a CNN for Multi-Class Supervised Classification

Activation Functions

More on CNN

Pre-Requisite For Working With Imagery Data

CNN on Image Data-Part 1

CNN on Image Data-Part 2

More on TFLearn

CNN Workflow for Keras

CNN With Keras

CNN on Image Data with Keras-Part 1

CNN on Image Data with Keras-Part 2

Transfer Learning

What is Transfer Learning?

Implement an InceptionV3 model on Real Images

Unsupervised Deep Learning

Simple Autoencoders

Add Sparsity Constraint


Reviews

S
Shahmeer8 October 2020

The course was spot on but the rather than having explanation of why particular code is being used, the author is just reading the written code.

K
Kevin26 August 2020

The preview is misleading, as the instructor in the preview was easy to understand, vs the instructor in the course who is harder to understand.

A
Anonymized19 August 2020

Amazing course. I feel that I am getting good knowledge and experience from this course which will help me in my endeavours.

M
Muna11 July 2020

Thank you for this course! I really liked the teaching style with the short exercises in video and practice exercises, which helped me to learn basics and clear my doubts in programming.

R
Robina10 July 2020

Thanks for the very well made course. The interactive part is very useful to get hand-on exercise to understand the content.

M
Mim18 February 2020

The material is really good! The concepts and examples are also very helpful. I am eagerly waiting to apply these in my office project!

M
Mitu17 February 2020

This is simply an incredible course to take for beginners. It takes you in depth into the theoretical concepts of image processing. As for the implementations, those discussed in great detail and given many important exercise for the student. All in all, an incredible course!

P
Pammi12 February 2020

Excellent method of teaching online! The video lectures, the sessions, resources are A+. I can see a lot of thought, research and time was put into this course. Being able to watch the videos and coding line by line with you made my work super easy! Thanks for making such quality course.

M
Mahbub29 January 2020

I'm really really glad I took this course. Not only is it fun, but the instructor is genuinely engaging and the material was great! The structure of the course is well thought out and all the help necessary are there to help anyone get through the course.

J
Jahed28 January 2020

I think this course is a great learning experience. I would definitely recommend it. The material and contents were presented in an easily-understood manner by the instructor. Keep it up!

M
Munmun27 January 2020

Excellent course on learning Image Processing using Python in an engaging, structured way. Very much enjoyed building my own apps and learning by doing. Instructor is entertaining and really makes it a great experience!

J
Jhumur27 January 2020

The course was fun and interesting, Can't wait to watch the next one! I Really appreciated the structure of this course. It really helps you to get a better understanding of image processing using python. Minerva is the best!

R
Rumana25 January 2020

Extraordinary experience with this course. Complete clear and brief introductions for image based image processing and computer vision. Very rich codes!

F
Fayssal19 January 2020

It is the best course to learn Image Processing on python, I am loving it.. Everything is covered in a great manner !

M
Muraj1 January 2020

My experience was really good! The content is great and the way he teaches is awesome! Useful resources, codes and sessions. Thanks a lot!


2250502

Udemy ID

3/2/2019

Course created date

9/16/2019

Course Indexed date
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