haceworld/Machine-learning-ML-Recommendation-system

Stars
3
Rank 3,963,521 (Top 79 %)
Language
Jupyter Notebook
Created almost 3 years ago
Updated almost 3 years ago

haceworld/Machine-learning-ML-Recommendation-system

haceworld

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Recommender systems are designed to recommend things to the user-based on several different factors. The recommender system deals with a large volume of information present by filtering the most important information based on the data provided by a user and other factors that take care of the user’s preference and interest.

haceworld

CRC-Coding-group

This is a group where I share my knowledge with my students based on Machine and deep learning applications

Jupyter Notebook

Canny-Edge-Detecction

Canny-Edge-Contrastive-Enhanced-Detection (CECED) implementation on single and multiple images

Jupyter Notebook

Template-Matching-using-OpenCV

Template Matching is a method for searching and finding the location of a template image in a larger image.

LBP

Local Binary Pattern (LBP) implementation on single and multiple images

Jupyter Notebook

Smoothing-using-OpenCV

How to smooth or blur images with OpenCV. Different morphological operations like 2D convolution ( image filtering ) and image blurring (image smoothing) using averaging, gaussian blurring, median blurring, bilateral filtering etc.

Neural-style-transfer

Neural style transfer is a neural algorithm of artistic style that manipulates digital images, or videos, in order to adopt the appearance or visual style of another image.

Jupyter Notebook

Resizing-Image-Dataset

This code helps to resize image Dataset in multiple folders at a time.

Jupyter Notebook

University-of-Electronic-Science-and-Technology-of-China-Master-Thesis-Overleaf-

This is the Overleaf Latex version of UESTC Master's Thesis for International postgraduate students who wish to format their postgraduate thesis using overleaf latex template rather than word template which is stressful and challenging

Multiple-rgb-images-to-grayscale-images

Conversion of multiple rgb images in a folder to grayscale images saved in another folder created

Jupyter Notebook

Fundamental-of-Machine-Learning

Fundamentals-of-Machine-Learning This repository introduces the basics of machine learning algorithms for preprocessing, regression and classification tasks covering the basic theory and common concepts and techniques involved in Machine Learning. This repository is for beginners who are interested in machine learning.

Jupyter Notebook

Operations-using-OpenCV

How to perform Bitwise Operations on Images. This includes bitwise AND, OR, NOT and XOR operations. This code will take you through on how to use Bitwise Operators (bitwise_and, bitwise_or, bitwise_xor, bitwise_not) in an image in OpenCV. Bitwise operations likebitwise_and(), bitwise_or(), bitwise_xor(), and bitwise_not() are useful when working with masks

Image-Pyramids-with-Python-and-OpenCV

How to use Image Pyramids with Python and OpenCV.

Combination-of-csv-extension-files

This helps to combine multiple csv extension files into a single csv file.

Jupyter Notebook

Object-detection-in-motion-using-OpenCV

Objection detection in motion using OpenCV Python

Edges-extraction

Extracting edges from multiple images

Jupyter Notebook

Lane-detection-with-OpenCV

Road Lane Line Detection with OpenCV .

Image-Data-Augmentation-in-Keras

Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset.

Jupyter Notebook

Siamese-Network

Siamese Network consists of two models with shared weights. Siamese Networks can be applied to different use cases, like detecting duplicates, finding anomalies, and re-identification.

extracting-contours-from-multiple-images

Extraction of contours from images

Jupyter Notebook

Super-Resolution-Convolutional-Neural-Network-SRCNN-

Super Resolution is the process of recovering a High Resolution (HR) image from a given Low Resolution (LR) image.

CLAHE

Contrast Limited Adaptive Histogram Equalization (CLAHE) implementation on single and multiple images

Jupyter Notebook

Contours-with-OpenCV

Finding and drawing contours using OpenCV in Python.

Kivy

Kivy is an open source Python framework for creating cross-platform multi-touch mobile applications with Natural User Interface.

Histogram-with-OpenCV

Histograms organize data into groups by counting how much data is in each group.

Image-Processing-Using-OpenCV

Open Source computer Vision (OpenCV) is one of the most widely used tool for image processing and computer vision tasks. This technique is utilized in numerous applications such as video capturing, face detection, object recognition, etc.

Hough-Transform-using-OpenCV

Understanding the concept of the Hough Transform and Hough Line Transform Theory.

Detecting-Fraud-Using-Neural-Network

Neural network algorithm is a powerful tool for detecting fraud. This simple code is put together to help researchers explore more possibilities beyond their imagination.

Jupyter Notebook

Object-and-Face-Detection-Using-OpenCV-and-Yolo

Implementation of OpenCV and YOLO face detection. You only look once (YOLO) is a state-of-the-art, real-time object detection system based on Deep Learning.

Mouse-Event-using-OpenCV

These Mouse events include mouse clicks (like left-button down, left-button up, left-button double-click etc) and movements over an attached OpenCV window. Capturing mouse click events with Python and OpenCV is easy. we just need to create a callback function and call this callback function using cv2.setMouseCallback('image', click_event_callback_function) method

University-of-Electronic-Science-and-Technology-of-China-Doctoral-Dissertation-Overleaf

This is the Overleaf Latex version of UESTC Ph.D Thesis for International postgraduate students who wish to format their postgraduate thesis using overleaf latex template rather than word template which is stressful and challenging

Machine-Learning-Stanford-University-Coursera

This contains course material and assignment solutions for the machine learning course from Stanford University - Coursera.

Trackbar-using-OpenCV

Few examples on how to use Trackbar as the Color Palette and changing colored image to grayscale image using Trackbar switch. You can also get user input with OpenCV trackbars.

Audio-Identification-and-Categorization

Audio(sound) classification can be referred to as the process of analyzing audio recordings. This amazing technique has multiple applications in the field of AI and data science such as chatbots, automated voice translators, virtual assistants, music genre identification, and text to speech applications.

Jupyter Notebook

Thresholding-and-masking-using-OpenCV

Image Thresholding is used for image segmentation.

wavelet-convolutional-Neural-Network

Haze-Removal-from-Images

Haze Removal can remove slight to extreme cases of haze affecting an image. Its most typical use is for landscape photography where the haze causes low contrast and low saturation, but it can also be used to improve images taken during rainy and foggy conditions.

Jupyter Notebook

University-of-Electronic-Science-and-Technology-of-China-Bachelor-Thesis-Overleaf

Well detailed Overleaf Latex version of University of Electronic Science and Technology of China (UESTC) Bachelor Thesis for International Undergraduate students who wish to format their final year thesis using overleaf latex template rather than the traditional methods which can be stressful and challenging.

Convolutional-Neural-Network

This repository contains CNN implementations.

Jupyter Notebook

Text-document-Categorization

As a common task in NLP, it permits the identification of free-text document based on pre-defined classes.

Jupyter Notebook

Fine-tuned-VGG16-for-Vehicle-classification

Vehicle classification using deep neural network

Jupyter Notebook

Convert-RGB-image-to-grayscale-image

In this repository, I will show you on the step by step procedure on how to convert RGB image to grayscale image

Jupyter Notebook

TensorFlow-Developer-Certification-Course

Jupyter Notebook

Deep-Learning

Jupyter Notebook

Image-Recognition

Image recognition refers to the task of inputting images into neural network with a predicted output result.

Jupyter Notebook

Cartoonify-Image-with-Machine-Learning

The objective of this machine learning project is to transform image(s) into its cartoon i.e. to CARTOONIFY the images using machine learning libraries.

read-multiple-images-and-save-in-a-different-folder

In this repository, I will show you the step by step procedure on how to read multiples images and save in a folder

Jupyter Notebook

Wavelet-CNN

Wavelet convolutional neural network combines a multi-resolution analysis and convolutional neural network into a single model to achieve computer vision task.

Jupyter Notebook

Read-and-Save-an-Image-to-a-different-folder

In this repository, I will show you the step by step procedure on how to read and save an image to a different folder

Jupyter Notebook

Convert-RGB-Images-to-HSV-images

In this repository, I will show you on the step by step procedure on how to convert RGB images to HSV images.

Jupyter Notebook

Fundamentals-of-Machine-Learning

Machine learning is a subset of artificial intelligence (AI) which focuses on the use of data and models to imitate the way that humans learn, gradually improving its accuracy performance..

Jupyter Notebook

Transfer-Learning-Models

Transfer learning is a technique to help solve this problem. As a concept, it works by transferring as much knowledge as possible from an existing model to a new model designed for a similar task. For example, transferring the more general aspects of a model which make up the main processes for completing a task.

Jupyter Notebook

Data-Science-Repo

All about Data Science and Data Analysis

Jupyter Notebook

Convert-RGB-images-to-Grayscale-Images

In this repository, I will show you on the step by step procedure on how to convert RGB images to grayscale images.

Jupyter Notebook

Curriculum-Vitae-CV-

Writing CV with LaTeX

Face-Recognition-with-Siamese-Network.

The model is trained based on face images from 8 different peoples

Jupyter Notebook

ESRGAN

Enhanced Super-resolution Generative Adversarial Network

Read-and-Display-an-Image-Image-Processing

This code will explain the step-by-step procedure on how to read and display image using OpenCV for beginners.

Jupyter Notebook

Numpy-

All About Numpy

Jupyter Notebook

Accessing-image-properties-in-OpenCV

In this repository, I will show you on the step by step procedure on how to read and display an image

Jupyter Notebook

CNN-Concatenation

This code concatenate two CNN networks from scratch

Jupyter Notebook

Enhancedd-Super-resolution-Generative-Adversarial-CNN

The model is trained based on face images from different peoples

Recommendation-Letter-Using-LaTex

Using LaTex to prepare a recommendation Letter

Convert-RGB-image-to-HSV-image

In this repository, I will show you on the step by step procedure on how to convert RGB image to HSV image.

Jupyter Notebook

Read-and-save-an-image-in-OpenCV-

In this repository, I will explain the step by step procedure on how to read and save an image.

Jupyter Notebook

Siamese-CNN

Siamese Network consists of two models with shared weights. Siamese Networks can be applied to different use cases, like detecting duplicates, finding anomalies, and re-identification.

Jupyter Notebook

Deep-Dream

DeepDream is an experiment that visualizes the patterns learned by a neural network. Similar to when a child watches clouds and tries to interpret random shapes. DeepDream over-interprets and enhances the patterns it sees in an image.

Jupyter Notebook

Read-Multiple-images-resize-and-Save-to-a-Folder

In this repository, I will show you on the step by step procedure on how to read Multiple images, resize and Save to a Folder

Jupyter Notebook

Automated-Image-Caption-Generator

Image caption generator is a process of recognizing the context of an image and annotating it with relevant captions using deep learning, and computer vision. It includes the labeling of an image with English keywords with the help of datasets provided during model training.

Jupyter Notebook

Machine-Learning-Specialization-by-Coursera

All about Machine Learning

Jupyter Notebook

Neural-Style-Transfer-2-

Neural Style Transfer deals with two sets of images: Content image and Style image. This technique helps to recreate the content image in the style of the reference image. It uses Neural Networks to apply the artistic style from one image to another.

Jupyter Notebook

Read-Resize-and-save-an-Image

In this repository, I will show you on the step by step procedure on how to read, resize and save an image

Jupyter Notebook

Image-Colorization

Image colorization is the process of taking an input grayscale (black and white) image and then producing an output colorized image that represents the semantic colors and tones of the input (for example, an ocean on a clear sunny day must be plausibly “blue” — it can’t be colored “hot pink” by the model).

Jupyter Notebook