Complete Python Based Image Processing and Computer Vision from Udemy

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

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.

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 &

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.

THIS ISN'

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.

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

What's inside

Learning objectives

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

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

Syllabus

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 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

Miscellaneous Lectures

Github Intro

Colab

What Is GCP?

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Students are expected to have basic knowledge and hands-on experience with Python programming and data structures

Examines computer vision, image processing, machine learning, and deep learning, which are the core skills for working with and analyzing image data

Introduces Tensorflow and Keras, which are open source libraries for building and training machine learning and deep learning models, making this course highly relevant to industry

Provides a comprehensive overview of image processing and computer vision techniques, including both traditional and deep learning approaches

Taught by Minerva Singh, who is an Oxford University and Cambridge University graduate with experience analyzing real-life data using data science techniques

Utilizes real imagery data, ensuring that students learn how to apply Python-based image processing in practical scenarios

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Complete Python Based Image Processing and Computer Vision with these activities:

Study group

Show steps

Engaging with peers will provide unique learning opportunities and improve retention, especially for students who may struggle with independently completing tasks.

Show steps

Find peers to create study group with.
Establish meeting times and topics.
Meet for study session and complete agreed upon topics.

Image processing basics review

Show steps

Familiarity with image processing basics is a common friction point for students. Reviewing the fundamentals will reduce this friction and improve foundational skills.

View Digital Image Processing, Global Edition on Amazon

Show steps

Read book chapters on image processing concepts.
Complete book exercises and problems.

Image recognition practice

Show steps

Students frequently encounter more difficulty with image recognition, and working on practice problems will increase familiarity and confidence.

Browse courses on Image Processing

Show steps

Find practice problems on image recognition.
Solve practice problems using learned concepts and methods.

Two other activities

Expand to see all activities and additional details

Show all five activities

Photo editing project

Show steps

Students will be able to apply all learned concepts to this practical project, giving them a fuller understanding of the scope and potential for their new skills

Browse courses on Image Processing

Show steps

Come up with a photo editing project idea.
Use Python and the skills learned in the course to implement the project.
Document and share the project.

Object segmentation tutorial

Show steps

Object segmentation provides a practical skill that can be applied in many real-world scenarios, and this guided tutorial will help students master this advanced concept.

Browse courses on Image Processing

Show steps

Find a guided tutorial on object segmentation.
Follow the tutorial, completing all examples and exercises.
Apply the learned techniques to a personal project.

Career center

Learners who complete Complete Python Based Image Processing and Computer Vision will develop knowledge and skills that may be useful to these careers:

Computer Vision Engineer

A Computer Vision Engineer builds, tests, and maintains software and systems that extract meaningful information from digital images and videos. This course can help with this by teaching you both traditional computer vision techniques using Python and OpenCV, as well as deep learning algorithms for image classification, and some unsupervised deep learning techniques like autoencoders.

See salaries and explore the career path for Computer Vision Engineer

Image Processing Engineer

An Image Processing Engineer designs, develops, and maintains software and systems that process images to enhance or extract useful information. This course will help prepare you with the skills for this position by providing instruction on conventional image processing techniques such as image filtering and transformations, as well as more advanced techniques like edge and corner detection. It also provides instruction in deep learning algorithms for image classification and segmentation.

See salaries and explore the career path for Image Processing Engineer

Data Analyst

A Data Analyst collects, processes, and analyzes data to extract insights and inform decision-making. This course will help build a foundation for this career by teaching you how to analyze data from images using Python and machine learning algorithms. You will also gain experience with tools like OpenCV for computer vision applications.

See salaries and explore the career path for Data Analyst

Research Scientist

A Research Scientist conducts research and develops new knowledge in a particular field. This course may be useful to you if you wish to specialize in image processing or computer vision. It will provide you with a foundation in the Python programming language and instruction in a range of data science and machine learning algorithms for image processing and computer vision.

See salaries and explore the career path for Research Scientist

Machine Learning Engineer

A Machine Learning Engineer designs, develops, deploys, and maintains machine learning models and systems. This course may be helpful by providing you with a foundation in the Python programming language, as well as instruction in machine learning algorithms used in image processing, such as PCA, K-means, and t-SNE, and deep learning with CNNs and autoencoders.

See salaries and explore the career path for Machine Learning Engineer

Statistician

A Statistician collects, analyzes, interprets, and presents data. This course may be useful for you if you wish to specialize in image processing or computer vision. It will provide you with a foundation in the Python programming language and instruction in a range of statistical techniques and machine learning algorithms for image processing and computer vision.

See salaries and explore the career path for Statistician

Computer Scientist

A Computer Scientist conducts research and develops new theories and techniques in computer science. This course may be useful by giving you instruction in a range of data science and machine learning algorithms for image processing and computer vision.

See salaries and explore the career path for Computer Scientist

Business Analyst

A Business Analyst analyzes business data to identify opportunities and improve processes. This course may be helpful by providing you with a foundation in the Python programming language and instruction in data analysis techniques that can be applied to business data, including image data.

See salaries and explore the career path for Business Analyst

Data Scientist

A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course will help prepare you with the skills of image processing with Python, which is a valuable tool for a Data Scientist. Additionally, since this course provides instruction on unsupervised and supervised learning, including deep learning, it may be helpful to you in gaining a foundational understanding of machine learning and its applications. Deep learning is revolutionizing Data Science and becoming an increasingly important skill.

See salaries and explore the career path for Data Scientist

Product Manager

A Product Manager plans, develops, and launches products. This course may be helpful for you if you are interested in developing products that use image processing or computer vision technology. It will provide you with a foundation in the Python programming language and instruction in data analysis techniques that can be applied to image data.

See salaries and explore the career path for Product Manager

Marketing Manager

A Marketing Manager plans and executes marketing campaigns to promote products or services. This course may be helpful by providing you with a foundation in the Python programming language and instruction in data analysis techniques that can be applied to marketing data, including image data.

See salaries and explore the career path for Marketing Manager

Software Engineer

A Software Engineer designs, develops, and maintains software systems. This course may be helpful to you as it provides a foundation in Python programming and instruction in a wide range of data science and machine learning algorithms for image processing and computer vision. Familiarity with these techniques and algorithms is valuable for a Software Engineer seeking to work with image data.

See salaries and explore the career path for Software Engineer

Sales Manager

A Sales Manager leads and manages a team of sales professionals to achieve sales targets. This course may be helpful by providing you with a foundation in the Python programming language and instruction in data analysis techniques that can be applied to sales data, including image data.

See salaries and explore the career path for Sales Manager

Operations Manager

An Operations Manager plans and executes operations to achieve business goals. This course may be helpful by providing you with a foundation in the Python programming language and instruction in data analysis techniques that can be applied to operational data, including image data.

See salaries and explore the career path for Operations Manager

Financial Analyst

A Financial Analyst analyzes financial data to make investment recommendations. This course may be helpful by providing you with a foundation in the Python programming language and instruction in data analysis techniques that can be applied to financial data, including image data.

See salaries and explore the career path for Financial Analyst

Complete Python Based Image Processing and Computer Vision

Here's a deal for you

What's inside

Learning objectives

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

Share

Similar courses