makraimit Goto Github PK

ajax-movie-recommendation-system-with-sentiment-analysis

Content-Based Recommender System recommends movies similar to the movie user likes and analyses the sentiments on the reviews given by the user for that movie.

amazon-rekognition-custom-labels-a2i-automated-continuous-model-improvement

With Amazon Rekognition Custom Labels, you can easily build and deploy Machine Learning (ML) models to identify custom objects which are specific to your business domain in images without requiring advanced ML knowledge. When combined with Amazon Augmented AI (A2I), you can quickly integrate a ML workflow to capture and label images with a human workforce for model training. As ML lifecycle is an iterative and repetitive process, you need to implement an effective workflow that can provide for continuous model training with new data and automated deployment. Your workflow also needs to be flexible enough to allow for changes without requiring development rework as your business objectives change. Operationalizing an effective and flexible workflow can be resource intensive, especially for customers who have limited machine learning capabilities. In this post, we will use AWS Step Functions, AWS Lambda, and AWS System Manager Parameter Store to automate a configurable ML workflow for Rekognition Custom Labels and A2I. We will provide an overview of the solution and instructions to deploy it with AWS CloudFormation.

amazon-rekognition-custom-labels-demo

A demo to test Custom Labels with models trained by Amazon Rekognition

amazon-sagemaker-custom-recommender-system

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

amazon-sagemaker-object-detection-from-scratch

Build a Custom Object Detection Model from Scratch with Amazon SageMaker and Deploy it at the Edge with AWS DeepLens. This workshop explains how you can leverage DeepLens to capture data at the edge and build a training data set with Amazon SageMaker Ground Truth. Then, train an object detection model with Amazon SageMaker and deploy it to AWS DeepLens.

amazon-textract-code-samples

Amazon Textract Code Samples

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

aws-sagemaker

aws-tutorial-code

AWS tutorial code.

bytedance-icme

code for 2019 bytedance icme

chartreader

Fully automated end-to-end framework to extract data from bar plots and other figures in scientific research papers using modules such as OpenCV, AWS-Rekognition.

cmu-multimodalsdk

CMU MultimodalSDK is a machine learning platform for development of advanced multimodal models as well as easily accessing and processing multimodal datasets.

coding-jin-optimistic

Python

cornac

A Comparative Framework for Multimodal Recommender Systems

cornernet

cross_sell-up_sell_recommender_system

A recommender system that enables cross-sell and upsell of products (either new products or already bought products) that will enable higher revenue generation. The data captures material that is sent to the wholesalers over a span of time.

deep-youtube-recommendations

Implementation of Youtube Recommendations Using Deep Learning

deepfashion2

DeepFashion2 Dataset https://arxiv.org/pdf/1901.07973.pdf

deeprule

eduvsum

EDUVSUM is a multimodal neural architecture that utilizes state-of-the-art audio, visual and textual features to identify important temporal segments in educational videos.

google-images-download

Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!

icme2019-ctr

The Code for ICME2019 Grand Challenge: Short Video Understanding (Single Model Ranks 6th)

icme2019_challenge

icme2019_challenge-dataset

image-copy-move-detection

Copy-move forgery detection on digital image using Python

lightning

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

makraimit

Config files for my GitHub profile.

mmgcn

MMGCN: Multi-modal Graph Convolution Network forPersonalized Recommendation of Micro-video

mrg

Code for the paper "Multimodal Review Generation for Recommender Systems", WWW'19

mvss-net

code for Image Manipulation Detection by Multi-View Multi-Scale Supervision