Artificial Intelligence && Deep Learning

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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https://medium.freecodecamp.org/how-to-be-a-great-programmer-34939494996d

How to be a great programmer

What sets apart the really great programmers?

5min read...

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https://medium.com/@rockyxu399/three-models-for-kaggles-flowers-recognition-dataset-bc2ff732cf4e

Three models for Kaggle’s “Flowers Recognition” Dataset (6 min read)

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https://medium.com/mathematical-beauty/deep-learning-for-cosmetics-2d1b427bbfa2

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, we’ll illustrate how three simple yet powerful ideas — geometric transformations, the triplet loss function and transfer learning — allow us to solve a variety of difficult inference problems with minimal human input.

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@DeepLearning_AI

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https://medium.com/@a.mirzaei69/adversarial-autoencoders-on-mnist-dataset-python-keras-implementation-5eeafd52ab21

Adversarial Autoencoders on MNIST dataset Python Keras Implementation

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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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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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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

Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data

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https://www.techsparks.co.in/hot-topic-for-project-and-thesis-machine-learning/

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Hot topic for project, thesis and research -- Machine Learning