Published On Aug 3, 2021
๐ฅ Edureka Machine Learning Certification training (Use Code: YOUTUBE20) : https://www.edureka.co/masters-progra...
This Edureka video on 'Building Document Scanner Using OpenCV' will give you an overview of Building Document Scanner Using OpenCV with Machine Learning and will help you understand various important concepts that concern Building Document Scanner Using OpenCV.
Following pointers are covered in this Building Document Scanner Using OpenCV tutorial:
1) Agenda 00:00
2) Problem Statement 00:50
3) Tools and Frameworks 01:52
3) Hands-on: Project 02:34
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--------Edureka Machine Learning Projects--------
๐ต Plant Leaf Disease Detection with GUI: https://bit.ly/36Y6l8g
๐ต House Price Prediction using ML: https://bit.ly/3i0VKzJ
๐ต Emoji Prediction using LSTM: https://bit.ly/2TDuPjR
๐ต Color old photographs using Autoencoders: https://bit.ly/3BQg7r9
๐ต Handwritten Digit Recognition on MNIST dataset: https://bit.ly/3zTCxGf
๐ต Generate Images Using DC-Gan's: https://bit.ly/2TPtYwC
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๐ตArtificial and Machine Learning PGD: https://bit.ly/2Ziy7b1
#edureka #edurekamachinelearning #machinelearning #CamScannerClone #machinelearningproject #machinelearningtutorial #edurekatraining
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How it Works?
1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate
About the Course :
Edurekaโs Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language.
Why Learn Machine Learning with Python?
Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
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