Complete Python Based Image Processing and Computer Vision
What you'll 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
Requirements
- The Ability To Install the Anaconda Environment On Your Computer/Laptop
- Know how to install and load packages in Anaconda
- Interest in Learning to Process Image Data
- Prior Exposure to Python Programming or Python Data Science Applications Will be Useful
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
Who this course is for:
- Students Interested In Getting Started With Image Processing and Computer Vision Applications In The Jupyter Environment
- Students Interested in Learning About the Theoretical Underpinnings of Image Processing and Computer Vision in a Jargon Free Manner.
- Students Interested in Learning the Practical Implementation of Common Image Processing and Computer Vision Tasks in Python
- Students Interested in Implementing Machine Learning Algorithms on Real Life Image Data
- Students Interested in getting Started With Tensorflow and Keras for Deep learning Applications
- Students Interested in Deploying Tensorflow and Keras For On Real Life Image Data
- Students Interested in Harnessing Transfer Learning For Their Own Image Analysis Projects
Instructor
- 4.4 Instructor Rating
- 20,353 Reviews
- 111,750 Students
- 53 Courses
I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year's experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics.
I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly regarded academic journals such as Remote Sensing and given guest lectures on prestigious forums such as Open Data Science Conference (ODSC).