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Sajid Ali's Projects

ivy icon ivy

Video-based object counting software.

labelme icon labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

learn-python icon learn-python

📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.

lightfm icon lightfm

A Python implementation of LightFM, a hybrid recommendation algorithm.

lime icon lime

Lime: Explaining the predictions of any machine learning classifier

machine-learning-notes icon machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习,概率模型和深度学习的讲义(2000+页)和视频链接

magpie icon magpie

Deep neural network framework for multi-label text classification

medicalzoopytorch icon medicalzoopytorch

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

medpy icon medpy

Medical image processing in Python

melissa-core icon melissa-core

A lovely virtual assistant for OS X, Windows and Linux systems.

miscnn icon miscnn

A framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning

moodle icon moodle

Moodle - the world's open source learning platform

nlp icon nlp

Natural language processing (NLP) is a subfield of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.

nlp-datasets icon nlp-datasets

Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)

objectron icon objectron

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

ocr icon ocr

Optical character recognition using neural network. Implemented with Python and its libraries Numpy and OpenCV.

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