Complete Python Based Image Processing and Computer Vision

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

4.41 (571 reviews)
Udemy
platform
English
language
Data & Analytics
category
instructor
Complete Python Based Image Processing and Computer Vision
8,900
students
5.5 hours
content
Nov 2023
last update
$74.99
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

Why take this course?

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 - Screenshot_01Complete Python Based Image Processing and Computer Vision - Screenshot_02Complete Python Based Image Processing and Computer Vision - Screenshot_03Complete Python Based Image Processing and Computer Vision - Screenshot_04

Our review

🌟 **Overall Course Review** 🌟 **Global Rating:** 4.48 The course in question has received a wide range of feedback from students, with an overall positive reception. The course is described as hands-on and practical, with several reviewers highlighting the potential real-world applications of the concepts taught. The instructor's expertise in the subject matter, particularly in image processing and computer vision using Python, has been frequently praised. ### Pros: - **Practical Applicability:** Many students found the course concepts to have great potential for practical use, indicating that the skills acquired are directly applicable to real-world problems in image processing and computer vision. - **Comprehensive Content:** The course is considered complete and comprehensive, covering valuable information that is significant in today's tech-driven environment. - **Instructor's Knowledge & Delivery:** The instructor is commended for their deep knowledge of the subject, clear delivery, and ability to explain finer details effectively. - **Engaging Presentation:** Several reviewers mentioned that the course is presented in an engaging manner, making learning more enjoyable. ### Cons: - **Teaching Methods:** A notable concern among students is the way the instructor delivers content, with some feeling that the lectures are too rapid for practical application and others criticizing the instructor for merely reading code without providing the underlying logic or explanations. - **Technical Issues:** Some technical issues have been reported, including outdated scripts, missing files, and unclear instructions on using specific commands like `ipython notebook`. - **Resource Availability:** There are complaints about the resources provided in the course, with missing files that have been requested by students for over a year without resolution. - **Course Preparation & Execution:** The course structure has been criticized for being poorly prepared in some aspects, with videos ending abruptly and lacking proper planning and editing. - **Documentation & Resources:** The documentation provided in Python scripts is reported to be poor, which can hinder the learning process. ### General Feedback: - **Beginner Suitability:** While the course is good for beginners with prior knowledge of Python and basic machine learning, some find that it lacks detailed explanations for those who are new to image processing. - **Practical Applicability:** The course is seen as having wide-ranging practical applicability, especially for professionals looking to enhance their work in the field of image processing and computer vision. ### Instructor Specific Feedback: - **Dr. Minerva:** Some students expressed gratitude towards Dr. Minerva for her contributions to the course and for teaching in an easy-to-understand manner. However, other feedback suggests that more detailed explanations would be beneficial. ### Recommendation: For those with a foundation in Python and image processing, this course appears to be a valuable resource that offers comprehensive knowledge and practical skills. However, potential students should be aware of the technical issues reported and consider whether they are prepared to address these on their own. The course would benefit from updates to scripts, improved video quality, better documentation, and more hands-on explanations for complex concepts. It's also recommended that the instructor reviews the feedback to further enhance the teaching methods and course structure for a more enriching learning experience.

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2250502
udemy ID
3/2/2019
course created date
9/16/2019
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