Hot topic for project, thesis and research -- Machine Learning
https://www.techsparks.co.in/hot-topic-for-project-and-thesis-machine-learning/
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Latest Thesis Topics in Machine Learning for Research Scholars
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Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
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Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-678c51b4b463
https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-678c51b4b463
Becoming Human
Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
The Most Complete List of Best AI Cheat Sheets
FOUNDATIONS OF MACHINE LEARNING
This book is a general introduction to machine learning that can serve as a textbook for students and researchers in the field.
It covers fundamental modern topics in machine learning while providing theoretical basis and conceptual tools needed for the discussion and justification algorithm.
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This book is a general introduction to machine learning that can serve as a textbook for students and researchers in the field.
It covers fundamental modern topics in machine learning while providing theoretical basis and conceptual tools needed for the discussion and justification algorithm.
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OpenCV By Example.pdf
14.6 MB
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This book covers:
Chapter 1, Getting Started with OpenCV.
Chapter 2, An Introduction to the Basics of OpenCV.
Chapter 3, Learning the Graphical User Interface and Basic Filtering.
Chapter 4, Delving into Histograms and Filters.
Chapter 5, Automated Optical Inspection, Object Segmentation, and Detection.
Chapter 6, Learning Object Classification
Chapter 7, Detecting Face Parts and Overlaying Masks,
Chapter 8, Video Surveillance, Background Modeling, and Morphological Operations,
Chapter 9, Learning Object Tracking
Chapter 10, Developing Segmentation Algorithms for Text Recognition,
Chapter 11, Text Recognition with Tesseract
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Chapter 1, Getting Started with OpenCV.
Chapter 2, An Introduction to the Basics of OpenCV.
Chapter 3, Learning the Graphical User Interface and Basic Filtering.
Chapter 4, Delving into Histograms and Filters.
Chapter 5, Automated Optical Inspection, Object Segmentation, and Detection.
Chapter 6, Learning Object Classification
Chapter 7, Detecting Face Parts and Overlaying Masks,
Chapter 8, Video Surveillance, Background Modeling, and Morphological Operations,
Chapter 9, Learning Object Tracking
Chapter 10, Developing Segmentation Algorithms for Text Recognition,
Chapter 11, Text Recognition with Tesseract
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https://medium.com/@a.mirzaei69/adversarial-autoencoders-on-mnist-dataset-python-keras-implementation-5eeafd52ab21
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https://medium.com/@a.mirzaei69/adversarial-autoencoders-on-mnist-dataset-python-keras-implementation-5eeafd52ab21
Medium
Adversarial Autoencoders on MNIST dataset Python Keras Implementation
The easy understanding of adversarial autoencoders: a combination of variational autoencoders and generative adversarial networks.
Deep Learning for Cosmetics
In this blog post, how we can use computer vision to solve a particularly poignant instance of this problem: finding influencers, images and videos that address a specific eye shape and complexion. Along the way, weβll illustrate how three simple yet powerful ideas β geometric transformations, the triplet loss function and transfer learning β allow us to solve a variety of difficult inference problems with minimal human input.
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In this blog post, how we can use computer vision to solve a particularly poignant instance of this problem: finding influencers, images and videos that address a specific eye shape and complexion. Along the way, weβll illustrate how three simple yet powerful ideas β geometric transformations, the triplet loss function and transfer learning β allow us to solve a variety of difficult inference problems with minimal human input.
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Three models for Kaggleβs βFlowers Recognitionβ Dataset (6 min read)
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https://medium.com/@rockyxu399/three-models-for-kaggles-flowers-recognition-dataset-bc2ff732cf4e
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https://medium.com/@rockyxu399/three-models-for-kaggles-flowers-recognition-dataset-bc2ff732cf4e
Medium
Three models for Kaggleβs βFlowers Recognitionβ Dataset
Model built from scratch, model built on VGG19 and model built on ResNet-50 for multi-class classification with 0.92 accuracy!
How to be a great programmer
What sets apart the really great programmers?
5min read...
What sets apart the really great programmers?
5min read...
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https://medium.freecodecamp.org/how-to-be-a-great-programmer-34939494996d
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https://medium.freecodecamp.org/how-to-be-a-great-programmer-34939494996d
freeCodeCamp.org
How to be a great programmer
by Amy M Haddad How to be a great programmer What sets apart the really great programmers? Photo by David Rangel [https://unsplash.com/photos/4m7gmLNr3M0?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText] on Unsplash [https://unsplash.cβ¦
Mastering OpenCV 3 (2nd edition)
Get hands-on with practical Computer Vision using OpenCV 3
This book covers :
Chapter 1, Cartoonifier and Skin Changer for Raspberry Pi
Chapter 2, Exploring Structure from Motion Using OpenCV
Chapter 3, Number Plate Recognition Using SVM and Neural Networks
Chapter 4, Non-Rigid Face Tracking
Chapter 5, 3D Head Pose Estimation Using AAM and POSIT
Chapter 6, Face Recognition Using Eigenfaces or Fisherfaces
Chapter 7, Natural Feature Tracking for Augmented Reality
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Get hands-on with practical Computer Vision using OpenCV 3
This book covers :
Chapter 1, Cartoonifier and Skin Changer for Raspberry Pi
Chapter 2, Exploring Structure from Motion Using OpenCV
Chapter 3, Number Plate Recognition Using SVM and Neural Networks
Chapter 4, Non-Rigid Face Tracking
Chapter 5, 3D Head Pose Estimation Using AAM and POSIT
Chapter 6, Face Recognition Using Eigenfaces or Fisherfaces
Chapter 7, Natural Feature Tracking for Augmented Reality
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