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3 Computer Vision courses
AI For Leaders
By Mpi Learning - Professional Learning And Development Provider
In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.
Certified Artificial Intelligence Practitioner
By Mpi Learning - Professional Learning And Development Provider
This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.
Why Should You Learn Machine Learning Its Significance, Working, and Roles
By garyv
Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune
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Show all 69PyTorch for Deep Learning and Computer Vision
By Packt
Learn to build highly sophisticated deep learning and Computer Vision applications with PyTorch
24 Hour Flash Deal **25-in-1 Computer Vision: C++ and OpenCV with GPU support Mega Bundle** Computer Vision: C++ and OpenCV with GPU support Enrolment Gifts **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter ** Take the initial steps toward a successful long-term career by studying the Computer Vision: C++ and OpenCV with GPU support package online with Studyhub through our online learning platform. The Computer Vision: C++ and OpenCV with GPU support bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass. This Computer Vision: C++ and OpenCV with GPU support course provides complete 360-degree training on Computer Vision: C++ and OpenCV with GPU support. You'll get not one, not two, not three, but twenty-five Computer Vision: C++ and OpenCV with GPU support courses included in this course. Plus Studyhub's signature Forever Access is given as always, meaning these Computer Vision: C++ and OpenCV with GPU support courses are yours for as long as you want them once you enrol in this course This Computer Vision: C++ and OpenCV with GPU support Bundle consists the following career oriented courses: Course 01: Computer Vision: C++ and OpenCV with GPU support Course 02: Python 3 Programming Course 03: Machine Learning Course with Python Course 04: Data Science & Machine Learning with R Course 05: Robotics - Sensors Course 06: Digital Electric Circuits & Intelligent Electrical Devices Course 07: AutoCAD Programming using VB.NET with Windows Forms Course 08: Learn MySQL from Scratch for Data Science and Analytics Course 09: Data Structure Course 10: Electronic Device and Circuits Protection Training Course 11: Computer Science with Python Course Course 12: IT Administration and Networking Course 13: Foundations of IT Security: Protecting Digital Assets Course 14: SQL Database Management Course 15: Deep Learning Neural Network with R Course 16: Computer Networks Security from Scratch to Advanced Course 17: Electronic & Electrical Devices Maintenance & Troubleshooting Course 18: Embedded Systems with 8051 Microcontroller Course 19: MATLAB Simulink for Electrical Power Engineering Course 20: Solidworks: Beginner to Advanced Course 21: Info Graphics Web Design - Affinity Designer Training Course 22: Diploma in Python Programming Course 23: Penetration Testing with OWASP ZAP: Mastery course Course 24: Unreal Engine 4 Course 25: Blender 3D Character Modeling & Rendering The Computer Vision: C++ and OpenCV with GPU support course has been prepared by focusing largely on Computer Vision: C++ and OpenCV with GPU support career readiness. It has been designed by our Computer Vision: C++ and OpenCV with GPU support specialists in a manner that you will be likely to find yourself head and shoulders above the others. For better learning, one to one assistance will also be provided if it's required by any learners. The Computer Vision: C++ and OpenCV with GPU support Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Computer Vision: C++ and OpenCV with GPU support bundle course has been created with twenty-five premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Computer Vision: C++ and OpenCV with GPU support Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Computer Vision: C++ and OpenCV with GPU support Elementary modules, allowing our students to grasp each lesson quickly. The Computer Vision: C++ and OpenCV with GPU support course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc. In this exclusive Computer Vision: C++ and OpenCV with GPU support bundle, you really hit the jackpot. Here's what you get: Step by step Computer Vision: C++ and OpenCV with GPU support lessons One to one assistance from Computer Vision: C++ and OpenCV with GPU supportprofessionals if you need it Innovative exams to test your knowledge after the Computer Vision: C++ and OpenCV with GPU supportcourse 24/7 customer support should you encounter any hiccups Top-class learning portal Unlimited lifetime access to all twenty-five Computer Vision: C++ and OpenCV with GPU support courses Digital Certificate, Transcript and student ID are all included in the price PDF certificate immediately after passing Original copies of your Computer Vision: C++ and OpenCV with GPU support certificate and transcript on the next working day Easily learn the Computer Vision: C++ and OpenCV with GPU support skills and knowledge you want from the comfort of your home CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Computer Vision: C++ and OpenCV with GPU support training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Computer Vision: C++ and OpenCV with GPU support Requirements To participate in this Computer Vision: C++ and OpenCV with GPU support course, all you need is - A smart device A secure internet connection And a keen interest in Computer Vision: C++ and OpenCV with GPU support Career path You will be able to kickstart your Computer Vision: C++ and OpenCV with GPU support career because this course includes various courses as a bonus. This Computer Vision: C++ and OpenCV with GPU support is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Computer Vision: C++ and OpenCV with GPU support career opportunities. Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free
Computer Vision: C++ and OpenCV with GPU support
By Course Cloud
The comprehensive Computer Vision: C++ and OpenCV with GPU support has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Computer Vision: C++ and OpenCV with GPU support today, and learn from the very best the industry has to offer! This best selling Computer Vision: C++ and OpenCV with GPU support has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Computer Vision: C++ and OpenCV with GPU support is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Computer Vision: C++ and OpenCV with GPU support is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Computer Vision: C++ and OpenCV with GPU support is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Computer Vision: C++ and OpenCV with GPU support, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Computer Vision: C++ and OpenCV with GPU support will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Computer Vision: C++ and OpenCV with GPU support to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.
The Computer Vision course with C++ and OpenCV with GPU support provides an introduction to computer vision and its applications using C++ and OpenCV with GPU acceleration. Students will learn about setting up the necessary environments, basic examples, background segmentation, object detection with OpenCV's ML module using C++ and CUDA, and optical flow. Learning Outcomes: Set up the required environments for C++ and OpenCV with GPU support. Understand the fundamentals of computer vision and its applications. Implement background segmentation techniques to extract relevant objects from the environment. Use OpenCV's ML module with C++ and CUDA to perform object detection efficiently. Apply optical flow algorithms to track object movements and analyze motion patterns. Why buy this Computer Vision: C++ and OpenCV with GPU support? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Computer Vision: C++ and OpenCV with GPU support there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Computer Vision: C++ and OpenCV with GPU support course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Computer Vision: C++ and OpenCV with GPU support does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Computer Vision: C++ and OpenCV with GPU support was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Computer Vision: C++ and OpenCV with GPU support is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 01: Set up Necesssary Environments Module 01: Driver installation 00:06:00 Module 02: Cuda toolkit installation 00:01:00 Module 03: Compile OpenCV from source with CUDA support part-1 00:06:00 Module 04: Compile OpenCV from source with CUDA support part-2 00:05:00 Module 05: Python environment for flownet2-pytorch 00:09:00 Unit 02: Introduction with a few basic examples! Module 01: Read camera & files in a folder (C++) 00:11:00 Module 02: Edge detection (C++) 00:08:00 Module 03: Color transformations (C++) 00:07:00 Module 04: Using a trackbar (C++) 00:06:00 Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++) 00:13:00 Unit 03: Background segmentation Module 01: Background segmentation with MOG (C++) 00:04:00 Module 02: MOG and MOG2 cuda implementation (C++ - CUDA) 00:03:00 Module 03: Special app: Track class 00:06:00 Module 04: Special app: Track bgseg Foreground objects 00:08:00 Unit 04: Object detection with openCV ML module (C++ CUDA) Module 01: A simple application to prepare dataset for object detection (C++) 00:08:00 Module 02: Train model with openCV ML module (C++ and CUDA) 00:13:00 Module 03: Object detection with openCV ML module (C++ CUDA) 00:06:00 Unit 05: Optical Flow Module 01: Optical flow with Farneback (C++) 00:08:00 Module 02: Optical flow with Farneback (C++ CUDA) 00:06:00 Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA) 00:05:00 Module 04: Optical flow with Nvidia Flownet2 (Python) 00:05:00 Module 05: Performance Comparison 00:07:00 Additional Resource Resources - Computer Vision: C++ and OpenCV with GPU support 00:00:00 Assignment Assignment - Computer Vision: C++ and OpenCV with GPU support 00:00:00
Computer Vision Theory and Projects in Python for Beginners
By Packt
Computer vision (CV), a subfield of computer science, focuses on replicating the complex functionalities of the human visual system. This course provides a comprehensive understanding of Computer Vision from the beginning using Python and helps you in becoming an expert.
Overview This comprehensive course on Computer Vision: C++ and OpenCV with GPU support will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Computer Vision: C++ and OpenCV with GPU support comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Computer Vision: C++ and OpenCV with GPU support. It is available to all students, of all academic backgrounds. Requirements Our Computer Vision: C++ and OpenCV with GPU support is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 5 sections • 22 lectures • 02:31:00 total length •Module 01: Driver installation: 00:06:00 •Module 02: Cuda toolkit installation: 00:01:00 •Module 03: Compile OpenCV from source with CUDA support part-1: 00:06:00 •Module 04: Compile OpenCV from source with CUDA support part-2: 00:05:00 •Module 05: Python environment for flownet2-pytorch: 00:09:00 •Module 01: Read camera & files in a folder (C++): 00:11:00 •Module 02: Edge detection (C++): 00:08:00 •Module 03: Color transformations (C++): 00:07:00 •Module 04: Using a trackbar (C++): 00:06:00 •Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++): 00:13:00 •Module 01: Background segmentation with MOG (C++): 00:04:00 •Module 02: MOG and MOG2 cuda implementation (C++ - CUDA): 00:03:00 •Module 03: Special app: Track class: 00:06:00 •Module 04: Special app: Track bgseg Foreground objects: 00:08:00 •Module 01: A simple application to prepare dataset for object detection (C++): 00:08:00 •Module 02: Train model with openCV ML module (C++ and CUDA): 00:13:00 •Module 03: Object detection with openCV ML module (C++ CUDA): 00:06:00 •Module 01: Optical flow with Farneback (C++): 00:08:00 •Module 02: Optical flow with Farneback (C++ CUDA): 00:06:00 •Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA): 00:05:00 •Module 04: Optical flow with Nvidia Flownet2 (Python): 00:05:00 •Module 05: Performance Comparison: 00:07:00
Deep Learning - Computer Vision for Beginners Using PyTorch
By Packt
In this course, you will be learning one of the widely used deep learning frameworks, that is, PyTorch, and learn the basics of convolutional neural networks in PyTorch. We will also cover the basics of Python and understand how to implement different Python libraries.
Computer Vision: Face Recognition Quick Starter in Python
By Packt
This course is designed for beginners or anyone who wants to get started with Python-based face recognition. In this course, you will learn how to perform face detection from images, face detection from real-time videos, emotion detection, age-gender prediction, face recognition from images and real-time videos, and more!
Computer Vision: Python OCR and Object Detection Quick Starter
By Packt
This course is a quick starter for anyone looking to delve into optical character recognition, image recognition, object detection, and object recognition using Python without having to deal with all the complexities and mathematics associated with a typical deep learning process.
