4.24 (440 reviews)
☑ 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
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
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
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
Face Detection With Haar Features: Theory
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
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
Supervised Learning: Classifying Images
Brief Introduction to Supervised Learning
Implement SVM to Classify Digits
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
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
What is Transfer Learning?
Implement an InceptionV3 model on Real Images
Unsupervised Deep Learning
Add Sparsity Constraint
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.
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.
Amazing course. I feel that I am getting good knowledge and experience from this course which will help me in my endeavours.
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.
Thanks for the very well made course. The interactive part is very useful to get hand-on exercise to understand the content.
The material is really good! The concepts and examples are also very helpful. I am eagerly waiting to apply these in my office project!
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!
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.
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.
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!
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!
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!
Extraordinary experience with this course. Complete clear and brief introductions for image based image processing and computer vision. Very rich codes!
It is the best course to learn Image Processing on python, I am loving it.. Everything is covered in a great manner !
My experience was really good! The content is great and the way he teaches is awesome! Useful resources, codes and sessions. Thanks a lot!