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ai-for-beginners

12 Weeks, 24 Lessons, AI for All!

ask_pdf_with_openai

attriclip

CVPR2023: AttriCLIP: A Non-Incremental Learner for Incremental Knowledge Learning

cnll-continual-noisy_label

Official Implementation of CVPR 2022 workshop paper "CNLL: A Semi-supervised Approach for Continual Noisy Label Learning"

computational-methods-of-optimization

deep-learning

PyTorch implementation of following: Transfer Learning, Feature Extraction from deep network, k-NN

digital-image-processing

Section-1 have following implementations: 1. Histogram Computation 2. Connected Component analysis 3. Image text extraction 4. Otsu binarization

dl-neural-style-transfer

Neural Style Transfer is one of the latest and most fascinating Deep Learning based application, in which we transfer style of one image to the content of another image using deep learning based on VGG-19 architecture. The result is a new image that combines the content of one image with the style of another.

dsa

dvpa

falcon-qamaster

image_segmentation

Segmentation based on similarity measure including Intensity difference and Distance of pixels. Also effect of rotation and addition of gaussian noise on segmentation is visualized using Matplotlib.

indictrans2

Translation models for 22 scheduled languages of India

infix-and-postfix-generator

learn-to-prompt-for-continual-learning

ViT, Prompt learning

machine-learning-implemetation-python

Basic Machine Learning implementation with python

meetingqa

mingpt

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

nepali-nlp-resources

Resources for Nepali Natural Language Processing

nlp

Translation task using NLP

nlp-reading-group

Everything related to the reading group.

nlp-zeo

oculus_car

'Oculus' mean Vision. This project deals with customized object detection viz. Cars, Stop Signs, animals, Person, Vehicles. Implemented using YOLOv4(You Only Look Once) algorithm, which was trained through custom weights specific to this application only.

optical-flow-interpolation

PyTorch implementation of the classical optical flow visualization by Baker et al. [ICCV 2007].

pca-tsne

TSNE is state of art method for visualization of data and PCA is also used for visualization of higher dimensional data by finding the most dominant eigen vectors

practicalnlpllms

pytorch

pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

sift_implementation

Implementation of Scale Invariant Feature Transform(SIFT) for feature detection

simclr

A PyTorch implementation of SimCLR based on ICML 2020 paper "A Simple Framework for Contrastive Learning of Visual Representations"